Jobs — Data Scientists

AI and Data Science Engineer II

Deloitte · Seattle, WA

Mid-level Master's

2026-06-04

WA 2026-06-04

Requirements

Bachelor's degree in engineering, mathematics, physics, machine learning, statistics, computer science, or another quantitative field
2+ years of industry experience outside of academia applying data science or machine learning methods
Experience translating business goals into machine learning use cases and model design
Experience performing exploratory data analysis and developing predictive models
Ability to travel 30%, on average, based on the work you do and the clients and industries/sectors you serve.
Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred

Master's degree in engineering, mathematics, physics, machine learning, statistics, computer science, or another quantitative field
Experience manipulating large marketing data sets and performing extract, transform, and load activities
Experience with boosted trees, logistic regression, classification techniques, unsupervised models, large language models, or experimental design
Experience with data sets generated in advertising technology or marketing technology environments
Experience presenting complex data insights to non-technical audiences
Experience with deep learning architectures or reinforcement learning
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $86,700 - $170,900.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: c205110ea9aa

AIML - ML Engineer, Responsible AI

Apple · Seattle, WA

Mid-level Doctorate

2026-06-04

WA 2026-06-04

Requirements

Strong engineering skills and experience in writing production-quality code in Python, Swift or other programming languages
Background in generative models, natural language processing, LLMs, or diffusion models
Experience with failure analysis, quality engineering, or robustness analysis for AI/ML based features
Experience working with crowd-based annotations and human evaluations
Experience working on explainability and interpretation of AI/ML models
Work with highly-sensitive content with exposure to offensive and controversial content

Preferred

BS, MS or PhD in Computer Science, Machine Learning, or related fields or an equivalent qualification acquired through other avenues
Proven track record of contributing to diverse teams in a collaborative environment

Responsibilities

Would you like to play a part in building the next generation of generative AI applications at Apple? We're looking for scientists and engineers to work on ambitious projects that will impact the future of Apple, our products, and the broader world.
In this role, you'll have the opportunity to tackle innovative problems in machine learning, particularly focused on generative AI. As a member of the Apple HCMI group, you will be working on Apple's generative models that will power a wide array of new features. Our team is currently working on large generative models for vision and language, with particular interest on safety, robustness, and uncertainty in models.
Develop models, tools, metrics, and datasets for assessing and evaluating the safety of generative models over the model deployment lifecycle
Develop methods, models, and tools to interpret and explain failures in language and diffusion models
Build and maintain human annotation and red teaming pipelines to assess quality and risk of various Apple products
Prototype, implement, and evaluate new ML models and algorithms for red teaming LLMs

View full posting on CareerOneStop → ID: 147f72c89925

Data Scientist - Pricing

Microsoft Corporation · Redmond, WA

Mid-level Doctorate

2026-06-04

WA 2026-06-04

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.

Preferred

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
Experience in Python, R, or similar languages
Experience with Azure Machine Learning (ML) or equivalent cloud-based ML platforms.
Experience working with large-scale data and distributed systems.
Experience with yield or revenue management, pricing optimization, or cloud resource allocation.
Data Science IC3 - The typical base pay range for this role across the U.S. is USD $102,100.00 - $202,200.00 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $133,800.00 - $219,200.00 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Responsibilities

Data Analysis & Modeling: Analyze large-scale datasets to identify patterns, trends, and opportunities for improving yield and efficiency.
Yield Optimization: Develop machine learning models to optimize resource allocation and pricing strategies.
Cross-Functional Collaboration: Partner with business planning, engineering, product management, and finance teams to align yield strategies with business objectives.
Experimentation & A/B Testing: Design and execute experiments to validate optimization hypotheses. Build causal inference models (e.g., difference-in-difference, synthetic control) to measure the impact of business decisions.
Data Visualization : Develop dashboards and other visuals to monitor key business trends, identify new opportunities, and translate findings to actionable insights.
Thought Leadership : Stay current with industry trends in AI, cloud economics, and optimization techniques; share insights and best practices internally.
Other : Embody our Culture (https://www.microsoft.com/en-us/about/corporate-values) and Values (https://careers.microsoft.com/us/en/culture)

View full posting on CareerOneStop → ID: 998bf2a4b542

Data Scientist I, Demand Forecasting

Amazon · Bellevue, WA

Entry-level Bachelor's

2026-06-04

WA 2026-06-04

Requirements

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
Bachelor's degree
Familiarity with large language models (LLMs) or generative AI applications in analytics or explainability

Preferred

Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
Experience with time series forecasting, demand modeling, or bias correction techniques

Responsibilities

Design and analyze experiments (A/B tests) to measure the impact of forecast model changes and SCOT initiatives, drawing causal inferences from both experimental and observational data
Develop bias correction models to improve forecast accuracy across Amazon's demand forecasting systems, including National, Regional, Grocery, SSD, Inbound, and CIV forecasts
Contribute to GenAI/LLM-based research for forecast explainability and interpretability, helping stakeholders understand what drives forecast signals
Support and enhance the Labs experimentation platform by building scalable inference and measurement solutions that quantify the impact of forecasting improvements
Work horizontally across the forecasting product portfolio and collaborate with product managers, applied scientists, and engineering teams to embed analytics and ML solutions where they create the most value
Use large datasets to build models addressing ambiguous forecasting questions, including demand prediction, out of stock, seasonality, and varying lead times and spans
Interpret data, write reports, and communicate measurement results to stakeholders by translating technical frameworks into business-oriented insights and actionable recommendations
Keys to success in this role include exceptional analytics, statistics, judgment, and communication skills. The candidate will need to be able to extract insights from data and clearly communicate appropriate triggers and actions
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
Medical, Dental, and Vision Coverage
Maternity and Parental Leave Options
Paid Time Off (PTO)
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!

View full posting on CareerOneStop → ID: 7583b72888d1

Machine Learning Engineer - News, Books, and Stocks Team

Apple · Seattle, WA

Mid-level Doctorate

2026-06-04

WA 2026-06-04

Requirements

MS in Machine Learning, Computer Science, or related field. Alternatively, equivalent industry experience to an MS degree is acceptable.
At least 2 years of experience shipping machine learning models in products.
Strong programming skills in Python, Java, or a related language, and one of the deep learning toolkits such as PyTorch, TensorFlow, or similar.
Ability to communicate effectively and collaborate with partner teams.
Commitment to encouraging an open and inclusive work environment.

Preferred

Ph.D. in Machine Learning, Computer Science, or related field.
At least 5 years of experience shipping machine learning models in products.
Experience with recommender systems.
Experience with text-centric AI/ML (LLMs, document classification, search, etc.)
Experience delivering high quality software at scale.
Experience designing user-facing machine learning features with interdisciplinary partners.

Responsibilities

In a time where the news and book media landscapes are changing by the day, Apple News and Apple Books stand as champions of quality content, expert curation, user privacy, and the judicious use of machine learning. Our lively and brilliant team consists of client and machine learning engineers who embody Apple's values. We inspire, teach, and otherwise enable each other to do the best work of our careers. Our team's outstanding retention rate speaks to our strong culture of respect for our teammates as both engineers and people. Would you like to work on such a team, solving hard problems in machine learning? Terrific! Please join us for the next generation of these apps!
Our team is seeking a high-energy and self-driven machine learning engineer who will play a central role in the delivery of scalable services. The team uses machine learning to tackle difficult and complicated problems in the news, books, and stocks domains, including text extraction, named entity recognition, duplicate detection, search, ranking, and much more! As a member of our dynamic group, you'll have the rare and rewarding opportunity to craft upcoming products that will delight and encourage millions of Apple's customers every day!

View full posting on CareerOneStop → ID: c912119310d9

Manager, Machine Learning Engineering - Ad Platforms

The Walt Disney Company · Seattle, WA

Manager Master's

2026-06-04

WA 2026-06-04

Requirements

Bachelor's or master's degree in computer science, Engineering,
Mathematics, Statistics, or a related field.
8+ years of relevant industry experience, with at least 2-3 years in a people-management or technical leadership role.
Proven ability to translate business problems into scalable ML and GenAI solutions and strong understanding of machine learning fundamentals, deep learning, and statistical modeling.
Proven experience designing, building, and deploying scalable machine learning models and systems in production.
Experience deploying ML/GenAI systems at scale using cloud platforms and MLOps practices
Advanced programming proficiency (e.g., Python, Java, or similar); experience with ML/DL frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face).
Experience building, fine-tuning, evaluating, and deploying LLM-based systems (e.g., RAG, prompt engineering, model optimization)
Demonstrated ability to lead global teams and collaborate across organizational boundaries.

Preferred

Domain knowledge in the Ad Tech industry
Experience working with large-scale data and distributed systems.
Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and MLOps pipelines.
Track record of innovation and contributions to the ML/AI community (publications, talks, open source).
The hiring range for this position in Los Angeles, CA area is $171,600 - $230,100 per year and Seattle Area is $179,700 - $241,000. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
*Job ID: 10152782

Responsibilities

You will apply your battle-tested experience, deep technical knowledge of software and systems including Machine Learning and AI technologies, and leadership skills to unblock and guide our ML/AI team members to design and build scalable, performant, maintainable, and testable models and pipelines in various domains using industry best practices which are aligned in close collaboration with the ML team in the US highlighting cross-functional collaboration.
Daily, you should bring:
A willingness and desire to effectively communicate and collaborate across teams and systems on architecture, design, and implementation.
A passion for mentoring, learning, and taking on new challenges.
A proven ability to work with product teams to translate requirements into
well-defined technical implementations, as well as the ability to define technical and operational metrics to measure system health.
A keen eye for potential optimizations and enhancements.
Kindness and pragmatic optimism.
A deep understanding of model development cycles and AI tool usage
Lead, mentor and guide Data Scientists, Machine Learning and AI engineers to build solutions adhering to industry best practices and deliver scalable solutions including model architecture and algorithm selection.
Lead by example and always strive to improve the design for more scalable, cleaner, and decoupled implementations.
Drive adoption of best practices in model development, code quality, testing, and documentation.
Solid understanding and usage of automated tools (AI) while adhering to company policy.
Define strategic direction for machine learning projects and collaborate with product and engineering stakeholders.
Oversee end-2-end machine learning workflow, including data collection, model development, deployment and modeling. These are expected to be aligned with the larger platform strategy and tools in collaboration with the global teams to stay consistent across Ad Platforms.
Foster innovation by exploring new ML techniques, tools, and technologies.
Communicate strategies, progress, and results to leadership and cross-functional teams.
Ensure responsible AI practices, including fairness, explainability, and compliance with privacy and ethical standards.
Develop partnerships across the organization to identify and prioritize high-impact ML opportunities.
Available for On-Call rotations based on the team's escalation policy and support schedule for ML/AI solutions

View full posting on CareerOneStop → ID: 0f8ff097436c

Senior Machine Learning Engineering Manager, Ad Platforms

The Walt Disney Company · Seattle, WA

Manager Master's

2026-06-04

WA 2026-06-04

Requirements

Bachelor's or master's degree in computer science, Engineering, Mathematics, Statistics, or a related field.
10+ years of relevant industry experience, with at least 5 years in people-management managing senior ICs and managers.
Proven ability to translate business problems into scalable ML and GenAI solutions and strong understanding of machine learning fundamentals, deep learning, and statistical modeling.
Proven experience designing, building, and deploying scalable machine learning models and systems in production.
Experience deploying ML/GenAI systems at scale using cloud platforms and MLOps practices
Advanced programming proficiency (e.g., Python, Java, or similar); experience with ML/DL frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face).
Experience building, fine-tuning, evaluating, and deploying LLM-based systems (e.g., RAG, prompt engineering, model optimization)
Demonstrated ability to lead global teams and collaborate across organizational boundaries.

Preferred

Domain knowledge in the Ad Tech industry
Experience working with large-scale data and distributed systems.
Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and MLOps pipelines.
Track record of innovation and contributions to the ML/AI community (publications, talks, open source).
The hiring range for this position in Los Angeles, CA area is $207,400 - $278,100 per year and Seattle Area is $217,300 - $291,500. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
*Job ID: 10152780

Responsibilities

You will apply your battle-tested experience, deep technical knowledge of software and systems including Machine Learning and AI technologies, and leadership skills to unblock and guide our ML/AI team members to design and build scalable, performant, maintainable, and testable models and pipelines in various domains using industry best practices which are aligned in close collaboration with the ML team in the US highlighting cross-functional collaboration.
Daily, you should bring:
A willingness and desire to effectively communicate and collaborate across teams and systems on architecture, design, and implementation.
A passion for mentoring, learning, and taking on new challenges.
A proven ability to work with product teams to translate requirements into
well-defined technical implementations, as well as the ability to define technical and operational metrics to measure system health.
A keen eye for potential optimizations and enhancements.
Kindness and pragmatic optimism.
A deep understanding of model development cycles and AI tool usage
Lead, mentor and guide senior individual contributors and managers across data scientists, machine learning and AI engineers teams to build solutions adhering to industry best practices and deliver scalable solutions including model architecture and algorithm selection.
Define strategic direction for machine learning projects and collaborate with product and engineering stakeholders.
Lead by example and always strive to improve the design for more scalable, cleaner, and decoupled implementations.
Drive adoption of best practices in model development, code quality, testing, and documentation.
Solid understanding and usage of automated tools (AI) while adhering to company policy.
Oversee end-2-end machine learning workflow, including data collection, model development, deployment and modeling. These are expected to be aligned with the larger platform strategy and tools in collaboration with the global teams to stay consistent across Ad Platforms.
Foster innovation by exploring new ML techniques, tools, and technologies.
Communicate strategies, progress, and results to leadership and cross-functional teams.
Ensure responsible AI practices, including fairness, explainability, and compliance with privacy and ethical standards.
Develop partnerships across the organization to identify and prioritize high-impact ML opportunities.
Available for On-Call rotations based on the team's escalation policy and support schedule for ML/AI solutions

View full posting on CareerOneStop → ID: f33cab28b6a2

Staff Machine Learning Engineer - News, Books, and Stocks Team

Apple · Seattle, WA

Senior Master's

2026-06-04

WA 2026-06-04

Requirements

MS in Machine Learning, Computer Science, or related field. Alternatively, equivalent industry experience to an MS degree is acceptable.
At least 5 years of experience shipping machine learning models in products.
Strong programming skills in Python, Java, or a related language, and one of the deep learning toolkits such as PyTorch, TensorFlow, or similar.
Experience designing user-facing machine learning features with interdisciplinary partners.
Experience with recommender systems.
Experience with text-centric AI/ML (LLMs, document classification, search, etc.)
Experience delivering high quality software at scale.
Ability to communicate effectively and collaborate with partner teams.
Commitment to encouraging an open and inclusive work environment.

Preferred

Experience in a technical leadership role.

Responsibilities

In a time where the news and book media landscapes are changing by the day, Apple News and
Apple Books stand as champions of quality content, expert curation, user privacy, and the
judicious use of machine learning.
Our lively and brilliant team consists of client and machine learning engineers who embody
Apple's values. We inspire, teach, and otherwise enable each other to do the best work of ou
Our team's outstanding retention rate speaks to our strong culture of respect for our teammates
as both engineers and people.
Would you like to work on such a team, solving hard problems in machine learning? Terrific!
Please join us for the next generation of these apps!
Our team is seeking a high-energy and self-driven machine learning engineer who will play a
central role in the delivery of scalable services. The team uses machine learning to tackle
difficult and complicated problems in the news, books, and stocks domains, including text
extraction, named entity recognition, duplicate detection, search, ranking, and much more! As a
member of our dynamic group, you'll have the rare and rewarding opportunity to craft upcoming
products that will delight and encourage millions of Apple's customers every day!

View full posting on CareerOneStop → ID: 056dfeed4396

Senior AI/ML Engineer - Future Sensing, Embodied AI

General Motors · Olympia, WA

Senior Bachelor's

2026-06-04

WA 2026-06-04

Preferred

Experience withperceptionsensors including cameras, radar, and lida
Experience with multi-modal sensor fusion and system integration
Experience with production ML pipelines, model optimization, and performance tuning
Experience with simulation, synthetic data, or scenario-based evaluation
Experience with architecting sensory systems or contributing to sensor placement and configuration studies
Experience deploying ML models into production or working within production ML environments
Experience in automotive, robotics, or safety-critical ML applications.
*Remote/Hybrid: This role is categorized as fully remote or hybrid.

Responsibilities

At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. Are you passionate about accelerating the future of autonomous driving? Join the Embodied AI team at General Motors. Our team is developing and deploying machine learning solutions that support safe and reliable autonomous vehicle behavior across real-world scenarios.
As a Senior AI/ML Future Sensing Engineer in the Embodied AI organization, you will develop and evaluate machine learning solutions contributing to future sensing architecture decisions and autonomous driving performance. You will contribute to designing and improving ML and perception models that support safe and reliable vehicle behavior across real-world scenarios, while helping connect sensing choices to measurable performance outcomes.
You will collaborate closely with senior engineers and cross-functional teams to translate research and technical concepts into production-ready or production-informing solutions while contributing to engineering best practices, technical analyses, and delivery execution.
*What You'll Do
Develop and improve AI/ML solutions aligned with GM's autonomous driving and future sensing objectives
Apply techniques such as unsupervised pre-training, imitation learning, reinforcement learning, model scaling and selection, and foundation modeling to solve problems in object detection, tracking, classification,perception, and safe AI
Develop and evaluateperceptionmodels and components for sensing studies involving cameras, lidar, radar, and multi-modal sensor fusion
Implement and evaluate models, incorporating research advancements into practical applications
Contribute to model training, fine-tuning, validation, debugging, and performance optimization forperceptionand sensor-fusion tasks
Help define and implement robust metrics for detection, reconstruction, localization support, semantic labeling, and model robustness under varied environmental conditions
Work with real and synthetic data to evaluate sensing tradeoffs across weather, lighting, occlusion, sensor noise, clutter, and near-field versus long-range scenarios
Contribute to production pipelines and technical workflows spanning data loading, model evaluation, error analysis, and deployment-oriented support
Collaborate with cross-functional teams to integrate models and algorithms into onboard driving systems and future sensing evaluation workflows
Participate in code reviews, documentation, and technical discussions to support engineering quality and knowledge sharing.
*Your Skills & Abilities
Bachelor's orMaster's degree in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field
Experience applying machine learning techniques to real-world systems or large-scale datasets
Experience building AI/ML or perception systems in autonomy, robotics, computer vision, or related domains
ProficiencyinPyTorchand Python
Experience working with model training pipelines or large-scale data processing workflows
Strong data processing skills using tools such as NumPy, Pandas, and Apache Spark
Experience with model validation, debugging, and failure analysis in ML orperceptionsettings
Experience with one or moreperceptiondomains such as object detection, segmentation, tracking, reconstruction, localization, or sensor fusion
Ability to collaborate effectively within cross-functional engineering teams.

View full posting on CareerOneStop → ID: a94913349ea5

Staff AI/ML Engineer - Future Sensing, Embodied AI

General Motors · Olympia, WA

Senior Doctorate

2026-06-04

WA 2026-06-04

Preferred

Experience in robotics or autonomous driving systems
Experience with architecting perception or sensory systems for automotive, robotics, or safety-critical platforms
Experience with system integration across sensors, calibration, compute, and onboard software pipelines
Experience with simulation, synthetic data, and sim-to-road evaluation workflows
Technical leadership experience including mentoring engineers and shaping major workstreams from concept to execution.
*Remote/Hybrid: This role is categorized as fully remote or hybrid.
*Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area.
The salary range for this role is $189,300.00 to $320,700.00. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
*Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
*Company Vehicle : Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

Responsibilities

At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. Are you passionate about accelerating the future of autonomous driving? Join the Embodied AI team at General Motors. Our team is developing and deploying machine learning solutions that support safe and reliable autonomous vehicle behavior across real-world scenarios.
As a Staff AI/ML Future Sensing Engineer in the Embodied AI organization, you will serve as a senior individual contributor driving end-to-end technical work that informs next-generation sensing architecture decisions. You will help define and evaluate machine learning and perception solutions that directly impact autonomous driving performance, with emphasis on future sensing architectures, multi-modal sensor fusion, system integration, and the technical evidence required to support sensor and compute decisions.
In this role, you will partner closely with cross-functional engineering teams, contribute to core technical direction within your domain, and support the growth of engineers through technical collaboration and mentorship. You will help translate research into scalable onboard ML and perception solutions while contributing to the continuous improvement of GM's autonomy stack and sensing strategy.
*What You'll Do
Design and implement AI/ML solutions aligned with GM's autonomous driving and future sensing objectives
Lead end-to-end technical studies across sensor selection, sensor configuration, sensor placement, and multi-modal sensor fusion using cameras, lidar, radar, and related sensing modalities
Architect and evaluateperceptionmodels and pipelines for detection, reconstruction, tracking, localization support, semantic labeling, and uncertainty estimation
Drive definition of robust model-level and system-level metrics used to compare sensor configurations, quantify subsystem differences, and evaluate performance parityrelativeto existing architectures
Lead model development efforts spanning data curation, training, validation, performance optimization, debugging, and deployment-oriented analysis
Partner with simulation teams to define synthetic-data and sensor-model requirements needed to evaluate future sensing concepts under adverse weather, sensor noise, occlusions, clutter, and near-field versus long-range scenarios
Drive system integration thinking across sensing, calibration, compute, software architecture, and vehicle constraints
Translate ambiguous architecture questions into concrete experiments, technical recommendations, and clear go / no-go evidence packages
Design and build efficient infrastructure, pipelines, and tooling to support large-scale data processing, model training, evaluation, and rapid iteration across teams
Drive technical execution from prototyping through integration and readiness for production adoption, documentinglearningsand best practices
Support and mentor engineers through technical collaboration and code reviews, fostering knowledge sharing and engineering excellence.
*Your Skills & Abilities
Bachelor's, Master's, or PhD in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field
Strong experience building and scaling AI/ML systems forperception, autonomy, robotics, or related real-world systems
Deep hands-on experience with modern deep learning frameworks such asPyTorchand strongproficiencyin Python
Experience working with model training pipelines, large-scale data workflows, and infrastructure enabling efficient model iteration across teams
Strong data processing skills using tools such as NumPy, Pandas, and Apache Spark
Strong experience with model validation, debugging, performance optimization, and error analysis under real-world constraints and timelines
Strong experience with multi-modal sensor fusion andperceptionpipelines using cameras, radar, lidar, or related sensing modalities
Experience defining metrics and evaluation methodologies forperceptionor autonomy systems
Strong communicationskills enabling effective collaboration across engineering teams
Experience deploying or preparing ML models for production environments and understanding end-to-end deployment workflows.

View full posting on CareerOneStop → ID: da61599829a0

Lead Data Science Engineer

HCSC · Helena, MT

Senior Doctorate

2026-06-04

MT 2026-06-04

Requirements

Bachelor degree and 5 years of work experience in a computer science, engineering, or related field OR Master's degree and 4 years of work experience in a computer science, engineering, or related field OR Ph.D. and 2 years of work experience in a computer science, engineering, or related field"
Learning and growth mindset.
Customer-focused.
Interpersonal, verbal and written communication skills.
Must demonstrate proficiency in at least five and mastery in one of the following six areas: data analysis and relational-style query languages; data pipelining and ETL; working with semi structured and unstructured data; a high- level programming language; distributed computing; understanding of healthcare.
Proficiency in iterative development practices.
Independently delivering or leading the delivery of data engineering solutions for multiple complex analytics or data science projects and products.
A track record of independently delivering or leading the delivery of ML engineering capabilities.
Experience in Python-based Data Science frameworks (LangChain, LangGraph, LangFuse).
Experience in Model evaluation and deployment.
Experience in data curation, prep, training, and fine-tuning of Models.
Experience in evaluation frameworks
Experience in prompt engineering
Experience in working with multiple Models

Preferred

Master degree in a computational field, or Bachelor degree with significant healthcare experience
Understanding PySpark / Databricks to efficiently work with large data sets
Azure Cloud Infrastructure / Deployment with emphasis on AI related tooling, Azure ML, Azure OpenAI, etc.
Experience in Observability Frameworks and Framework Operationalization.
Experience in creation of knowledge graph database (neo4J)
Experience in working with Small Language Models or custom Models
*Are you being referred to one of our roles? If so, ask your connection at HCSC about our Employee Referral process!

Responsibilities

This position is responsible for the engineering work necessary for successful creation, deployment and managing of AI capabilities of the Intelligent Delivery Platform. This includes
ensuring data quality,
creation of new data pipelines,
optimization and management of existing data pipelines,
ingestion and curation of data sources for Gen AI purposes (including chunking/embedding strategies for RAG system),
AI Agent delivery,
Prompt Engineering,
selection and configuration of AI-specific tools and platforms
management and monitoring of AI models through MLOps tools and model ops practices.
To operationalize AI capabilities, they will work closely with larger team who will supplement where traditional application development support is needed.
*NOTE: This hybrid role can be located in CHICAGO IL; WAUKEGAN, IL; TULSA, OK; HELENA, MT; ALBUQUERQUE, NM; or RICHARDSON, TX ~ relocation will not be offered; sponsorship is not available.

View full posting on CareerOneStop → ID: 7af06db303cc

Machine Learning Engineering Manager

Indeed · Seattle, WA

Manager Doctorate

2026-06-03

WA 2026-06-03

Responsibilities

At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
Work to understand, prioritize, and plan the team's work items without external guidance.
Ensure delivery of machine learning solutions, set expectations for what can be done and by when, and prioritize incoming projects.
Improve existing Agile, ML, and A/B testing processes and develop new ones.
Scope projects, gather and improve on requirements, and delegate work effectively.
Partner with and provide project direction and feedback to cross-functional peers, including Product Managers, Software Engineers.
Remove roadblocks and give individual contributors autonomy and ownership.
Brainstorm with teammates about practical experimental design, navigating production codebases, and model development.
Be prepared to closely engage and contribute directly to implementation when necessary.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with a minimum of 3 years experience
Demonstrated achievement as a Manager in Machine Learning Engineering, overseeing teams of 3 or more, and addressing intricate, large-scale problems
Well-versed in coding (Python, Java, Go, or C++) and experience with SQL Databases like Presto, and data processing frameworks like Spark
Have full-stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring
Highly effective in coaching Machine Learning Engineers, facilitating qualification enhancement, and fostering career development

View full posting on CareerOneStop → ID: 85c5b878e3fc

Senior Machine Learning Engineer

Indeed · Seattle, WA

Senior Doctorate

2026-06-03

WA 2026-06-03

Responsibilities

As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to drive value and better customer experiences for our Sourcing product, which connects employers with new talent through AI. This Senior MLE will help us improve our automated outreach quality, building new agentic experiences, and LLMOps reliability and infrastructure.
Autonomously deliver ML and AI projects, including prompt development and evaluation, training ML models, building LLM-as-a-Judge capabilities, and building recommendation / ranking systems
Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our Sourcing product
Estimate potential business impact of AI and ML and balance tradeoffs between delivery velocity and systematic infrastructure investments
Collaborate with cross-functional partners, including Machine Learning Engineers, Data Scientists, Software Engineers, Product, and UX designers/researchers
Define and implement evaluation, observability, and production monitoring approaches for ML and LLM-based systems.
Serve as a trusted partner and communicator for cross-functional and cross-team counterparts, translating technical concepts to facilitate productive collaboration.
Mentor other Machine Learning Engineers, Data Scientists, and Software Engineers on the team
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 5 years of related experience; or a Master's degree with a minimum of 3 years of experience; or a PhD without experience
Prior success in deploying impactful Machine Learning and/or LLM-based solutions to large-scale production systems
Solid knowledge of data structures and algorithms
Demonstrated sense of ownership and accountability as a key contributor in the technical and product domains
Familiarity with agent orchestration frameworks, LLM observability tools, and prompt optimization techniques (e.g. GEPA)
Knowledge of and practical experience working on Deep Learning libraries (like Torch, Tensorflow, etc.) and modern ML/LLM tooling
Familiarity with modern ML system design, including evaluation, experimentation, and production monitoring for predictive and LLM-based systems
Excellent written and verbal communication, effective with technical and business audiences

View full posting on CareerOneStop → ID: 6e8b5bdf474e

Principal Machine Learning Engineer

Oracle · Olympia, WA

Senior Master's

2026-06-03

WA 2026-06-03

Requirements

BS/MS in Computer Science or equivalent experience
6-10+ years building and shipping enterprise distributed or cloud-native systems
Experience scaling heterogeneous CPU/GPU training infrastructure for large multimodal frontier models
Strong foundation in system design, distributed systems, and cloud architecture best practices
Proficiency in Java, Python, or similar object-oriented languages
Experience building highly available services using service-oriented design patterns and service-to-service communication protocols
Proven ability to deliver impact in collaborative, fast-paced environments
Strong verbal and written communication skills, including technical design documentation
Hands-on experience with containers and orchestration technologies such as Kubernetes and Docke

Preferred

Production experience with Cloud and ML technologies
Experience working in the below areas and algorithms will be ideal but not mandatory:?
Generative AI Modeling: Customizing LLM's, build and deploy LLM's at scale for large scale data generation
Algorithms: Transformer models, Attention mechanism, Prompt tooling

Responsibilities

At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world.
Values are OCI's foundation and how we deliver excellence. We strive for equity, inclusion, and respect for all. We are committed to the greater good in our products and our actions. We are constantly learning and taking opportunities to grow our careers and ourselves. We challenge each other to stretch beyond our past to build our future.
You are the builder here. You will be part of a team of smart, motivated, and diverse people and given the autonomy and support to do your best work. It is a dynamic and flexible workplace where you'll belong and be encouraged.
In? OCI ? AI Infrastructure ?org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. In this role, you will drive building state-of-the-art training infrastructure for massive GPU clusters, as well as designing agentic systems deployed on OCI infrastructure at enterprise-scale. You will be innovating on leading principles of agentic software development and driving the frontier on infrastructure that maximizes the potential of bleeding-edge GPU clusters.
We are working at the forefront of Generative AI (GenAI) landscape working with teams across Oracle on multi-modal data generation and leading the framework across Oracle.
Design and develop AI software in Java, Python, and other languages.?
Participate in the entire software lifecycle - development, testing, CI/CD and production operations
Participate in the entire model development cycle - training, fine-tuning, model serving, evaluation/benchmarking and human preference learning.
Apply engineering principles for defining robust and maintainable architectures and designs.?
Build cloud service on top of the modern Infrastructure as Service (IaaS) building blocks at OCI
Design and build distributed, scalable, fault tolerant software systems to facilitate development of GenAI models.
Identify requirements, scope solutions, estimate work, schedule deliverables. Help establish and drive the adoption of outstanding coding standards and patterns and help enhance our inclusive engineering culture.
Contribute to publications, blogs and open-source ML performance submissions partnering with product managers
Balance between product feature development and production operational concerns like ops automation, structured logging, instrumentation for metrics and participating in on-call.

View full posting on CareerOneStop → ID: 5fada611e570

Machine Learning Engineering Manager

Indeed · Portland, OR

Manager Doctorate

2026-06-03

WA 2026-06-03

Responsibilities

At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
Work to understand, prioritize, and plan the team's work items without external guidance.
Ensure delivery of machine learning solutions, set expectations for what can be done and by when, and prioritize incoming projects.
Improve existing Agile, ML, and A/B testing processes and develop new ones.
Scope projects, gather and improve on requirements, and delegate work effectively.
Partner with and provide project direction and feedback to cross-functional peers, including Product Managers, Software Engineers.
Remove roadblocks and give individual contributors autonomy and ownership.
Brainstorm with teammates about practical experimental design, navigating production codebases, and model development.
Be prepared to closely engage and contribute directly to implementation when necessary.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with a minimum of 3 years experience
Demonstrated achievement as a Manager in Machine Learning Engineering, overseeing teams of 3 or more, and addressing intricate, large-scale problems
Well-versed in coding (Python, Java, Go, or C++) and experience with SQL Databases like Presto, and data processing frameworks like Spark
Have full-stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring
Highly effective in coaching Machine Learning Engineers, facilitating qualification enhancement, and fostering career development

View full posting on CareerOneStop → ID: 1dab31464fa0

Senior Machine Learning Engineer

Indeed · Portland, OR

Senior Doctorate

2026-06-03

WA 2026-06-03

Responsibilities

As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to drive value and better customer experiences for our Sourcing product, which connects employers with new talent through AI. This Senior MLE will help us improve our automated outreach quality, building new agentic experiences, and LLMOps reliability and infrastructure.
Autonomously deliver ML and AI projects, including prompt development and evaluation, training ML models, building LLM-as-a-Judge capabilities, and building recommendation / ranking systems
Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our Sourcing product
Estimate potential business impact of AI and ML and balance tradeoffs between delivery velocity and systematic infrastructure investments
Collaborate with cross-functional partners, including Machine Learning Engineers, Data Scientists, Software Engineers, Product, and UX designers/researchers
Define and implement evaluation, observability, and production monitoring approaches for ML and LLM-based systems.
Serve as a trusted partner and communicator for cross-functional and cross-team counterparts, translating technical concepts to facilitate productive collaboration.
Mentor other Machine Learning Engineers, Data Scientists, and Software Engineers on the team
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 5 years of related experience; or a Master's degree with a minimum of 3 years of experience; or a PhD without experience
Prior success in deploying impactful Machine Learning and/or LLM-based solutions to large-scale production systems
Solid knowledge of data structures and algorithms
Demonstrated sense of ownership and accountability as a key contributor in the technical and product domains
Familiarity with agent orchestration frameworks, LLM observability tools, and prompt optimization techniques (e.g. GEPA)
Knowledge of and practical experience working on Deep Learning libraries (like Torch, Tensorflow, etc.) and modern ML/LLM tooling
Familiarity with modern ML system design, including evaluation, experimentation, and production monitoring for predictive and LLM-based systems
Excellent written and verbal communication, effective with technical and business audiences

View full posting on CareerOneStop → ID: 40587d39cb8e

Machine Learning Engineering Manager

Indeed · Boise, ID

Manager Doctorate

2026-06-03

ID 2026-06-03

Responsibilities

At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
Work to understand, prioritize, and plan the team's work items without external guidance.
Ensure delivery of machine learning solutions, set expectations for what can be done and by when, and prioritize incoming projects.
Improve existing Agile, ML, and A/B testing processes and develop new ones.
Scope projects, gather and improve on requirements, and delegate work effectively.
Partner with and provide project direction and feedback to cross-functional peers, including Product Managers, Software Engineers.
Remove roadblocks and give individual contributors autonomy and ownership.
Brainstorm with teammates about practical experimental design, navigating production codebases, and model development.
Be prepared to closely engage and contribute directly to implementation when necessary.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with a minimum of 3 years experience
Demonstrated achievement as a Manager in Machine Learning Engineering, overseeing teams of 3 or more, and addressing intricate, large-scale problems
Well-versed in coding (Python, Java, Go, or C++) and experience with SQL Databases like Presto, and data processing frameworks like Spark
Have full-stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring
Highly effective in coaching Machine Learning Engineers, facilitating qualification enhancement, and fostering career development

View full posting on CareerOneStop → ID: fa90c2d42649

Principal Machine Learning Engineer

Oracle · Boise, ID

Senior Master's

2026-06-03

ID 2026-06-03

Requirements

BS/MS in Computer Science or equivalent experience
6-10+ years building and shipping enterprise distributed or cloud-native systems
Experience scaling heterogeneous CPU/GPU training infrastructure for large multimodal frontier models
Strong foundation in system design, distributed systems, and cloud architecture best practices
Proficiency in Java, Python, or similar object-oriented languages
Experience building highly available services using service-oriented design patterns and service-to-service communication protocols
Proven ability to deliver impact in collaborative, fast-paced environments
Strong verbal and written communication skills, including technical design documentation
Hands-on experience with containers and orchestration technologies such as Kubernetes and Docke

Preferred

Production experience with Cloud and ML technologies
Experience working in the below areas and algorithms will be ideal but not mandatory:?
Generative AI Modeling: Customizing LLM's, build and deploy LLM's at scale for large scale data generation
Algorithms: Transformer models, Attention mechanism, Prompt tooling

Responsibilities

At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world.
Values are OCI's foundation and how we deliver excellence. We strive for equity, inclusion, and respect for all. We are committed to the greater good in our products and our actions. We are constantly learning and taking opportunities to grow our careers and ourselves. We challenge each other to stretch beyond our past to build our future.
You are the builder here. You will be part of a team of smart, motivated, and diverse people and given the autonomy and support to do your best work. It is a dynamic and flexible workplace where you'll belong and be encouraged.
In? OCI ? AI Infrastructure ?org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. In this role, you will drive building state-of-the-art training infrastructure for massive GPU clusters, as well as designing agentic systems deployed on OCI infrastructure at enterprise-scale. You will be innovating on leading principles of agentic software development and driving the frontier on infrastructure that maximizes the potential of bleeding-edge GPU clusters.
We are working at the forefront of Generative AI (GenAI) landscape working with teams across Oracle on multi-modal data generation and leading the framework across Oracle.
Design and develop AI software in Java, Python, and other languages.?
Participate in the entire software lifecycle - development, testing, CI/CD and production operations
Participate in the entire model development cycle - training, fine-tuning, model serving, evaluation/benchmarking and human preference learning.
Apply engineering principles for defining robust and maintainable architectures and designs.?
Build cloud service on top of the modern Infrastructure as Service (IaaS) building blocks at OCI
Design and build distributed, scalable, fault tolerant software systems to facilitate development of GenAI models.
Identify requirements, scope solutions, estimate work, schedule deliverables. Help establish and drive the adoption of outstanding coding standards and patterns and help enhance our inclusive engineering culture.
Contribute to publications, blogs and open-source ML performance submissions partnering with product managers
Balance between product feature development and production operational concerns like ops automation, structured logging, instrumentation for metrics and participating in on-call.

View full posting on CareerOneStop → ID: 59e51d431663

Senior Machine Learning Engineer

Indeed · Boise, ID

Senior Doctorate

2026-06-03

ID 2026-06-03

Responsibilities

As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to drive value and better customer experiences for our Sourcing product, which connects employers with new talent through AI. This Senior MLE will help us improve our automated outreach quality, building new agentic experiences, and LLMOps reliability and infrastructure.
Autonomously deliver ML and AI projects, including prompt development and evaluation, training ML models, building LLM-as-a-Judge capabilities, and building recommendation / ranking systems
Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our Sourcing product
Estimate potential business impact of AI and ML and balance tradeoffs between delivery velocity and systematic infrastructure investments
Collaborate with cross-functional partners, including Machine Learning Engineers, Data Scientists, Software Engineers, Product, and UX designers/researchers
Define and implement evaluation, observability, and production monitoring approaches for ML and LLM-based systems.
Serve as a trusted partner and communicator for cross-functional and cross-team counterparts, translating technical concepts to facilitate productive collaboration.
Mentor other Machine Learning Engineers, Data Scientists, and Software Engineers on the team
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 5 years of related experience; or a Master's degree with a minimum of 3 years of experience; or a PhD without experience
Prior success in deploying impactful Machine Learning and/or LLM-based solutions to large-scale production systems
Solid knowledge of data structures and algorithms
Demonstrated sense of ownership and accountability as a key contributor in the technical and product domains
Familiarity with agent orchestration frameworks, LLM observability tools, and prompt optimization techniques (e.g. GEPA)
Knowledge of and practical experience working on Deep Learning libraries (like Torch, Tensorflow, etc.) and modern ML/LLM tooling
Familiarity with modern ML system design, including evaluation, experimentation, and production monitoring for predictive and LLM-based systems
Excellent written and verbal communication, effective with technical and business audiences

View full posting on CareerOneStop → ID: 6dd1d09b0662

Staff Data Scientist

Micron Technology, Inc. · Boise, ID

Senior Doctorate

2026-06-03

ID 2026-06-03

Requirements

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Finance, Economics, or a related quantitative field, plus 5+ years of experience in data science, machine learning, or advanced analytics roles.
Strong proficiency in Python and SQL, with hands-on experience developing, testing, and deploying predictive or statistical models on large, complex datasets.
Working knowledge of core data science and AI/ML tools, including Python libraries such as pandas, NumPy, and scikit-learn, with hands-on experience in Snowflake, Streamlit, and modern AI/ML development environments.
Experience working with Finance-related data, workflows, and business needs, including corporate finance, P&L, and manufacturing cost data, as well as forecasting, variance analysis, scenario planning, actuals-to-forecast reconciliation, or financial waterfall reporting.
Experience partnering with Finance stakeholders and cross-functional teams to deliver scalable, user-adopted solutions, and providing technical leadership or mentorship to data scientists and analysts.

Preferred

Advanced degree (Master's or PhD) in Data Science, Computer Science, Statistics, Mathematics, Operations Research, Finance, Economics, or a related quantitative discipline.
Experience applying advanced machine learning, time series modeling, optimization, or AI techniques to Finance-related data, workflows, and business needs, including corporate finance, P&L, manufacturing cost data, forecasting, scenario modeling, driver analysis, or decision support.
Hands-on experience developing, deploying, and monitoring conversational AI agents or LLM-based solutions in Snowflake, cloud, or similar enterprise data environments, including prompt/instruction design, evaluation, and performance optimization.
Experience translating finance business logic into production-grade analytical applications, model features, prompts, rules, or agent workflows that support scalable decision-making.
Experience with data visualization and basic UI development, including creating intuitive dashboards, analytical interfaces, or lightweight front-end experiences that improve how Finance users interact with models, insights, and AI-enabled solutions.
The US base salary range that Micron Technology estimates it could pay for this full-time position is:
$123,000.00 - $290,000.00 a yea
Additional compensation may include benefits, bonuses and equity.
Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target base pay for new hire salaries of the position across all US locations. Within the range, individual pay is determined by work location and additional job-related factors, including knowledge, skills, experience, tenure and relevant education or training. The pay scale is subject to change depending on business needs. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
As a world leader in the semiconductor industry, Micron is dedicated to your personal wellbeing and professional growth. Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time-off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on micron.com/careers/benefits .

Responsibilities

Lead the development of predictive models for finance use cases, including:
Forecasting (revenue, expenses, cost drivers)
Variance analysis (actuals vs. plan, drivers of deviation)
Scenario modeling and sensitivity analysis to support business planning
Build and implement scalable, production-grade analytical models that integrate with enterprise finance systems and data platforms
Develop, test, and deploy intelligent agents in a Snowflake environment, including:
Agent-based workflows for finance analytics use cases
Prompt design, evaluation frameworks, and performance testing
Monitoring and continuous improvement of agent outputs
Partner closely with Finance business stakeholders, Data Engineering, and UX teams to:
Translate business problems into data science solutions
Define success metrics and validate model performance
Drive adoption of analytics and AI capabilities
Build and optimize data pipelines and modeling workflows to clean, combine, and analyze vast, detailed data compilations from multiple sources
Lead exploratory analysis and prototype development to identify new opportunities for automation, insight generation, and decision support
Provide technical leadership and mentorship to junior data scientists, setting best practices for modeling, experimentation, and product ionization

View full posting on CareerOneStop → ID: 7481962dd4f6

Staff Machine Learning Engineer

Micron Technology, Inc. · Boise, ID

Senior Master's

2026-06-03

ID 2026-06-03

Our vision is to transform how the world uses information to enrich life for _all_ . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and adva

View full posting on CareerOneStop → ID: fc816a13d902

Principal Machine Learning Engineer

Oracle · Salem, OR

Senior Master's

2026-06-03

OR 2026-06-03

Requirements

BS/MS in Computer Science or equivalent experience
6-10+ years building and shipping enterprise distributed or cloud-native systems
Experience scaling heterogeneous CPU/GPU training infrastructure for large multimodal frontier models
Strong foundation in system design, distributed systems, and cloud architecture best practices
Proficiency in Java, Python, or similar object-oriented languages
Experience building highly available services using service-oriented design patterns and service-to-service communication protocols
Proven ability to deliver impact in collaborative, fast-paced environments
Strong verbal and written communication skills, including technical design documentation
Hands-on experience with containers and orchestration technologies such as Kubernetes and Docke

Preferred

Production experience with Cloud and ML technologies
Experience working in the below areas and algorithms will be ideal but not mandatory:?
Generative AI Modeling: Customizing LLM's, build and deploy LLM's at scale for large scale data generation
Algorithms: Transformer models, Attention mechanism, Prompt tooling

Responsibilities

At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world.
Values are OCI's foundation and how we deliver excellence. We strive for equity, inclusion, and respect for all. We are committed to the greater good in our products and our actions. We are constantly learning and taking opportunities to grow our careers and ourselves. We challenge each other to stretch beyond our past to build our future.
You are the builder here. You will be part of a team of smart, motivated, and diverse people and given the autonomy and support to do your best work. It is a dynamic and flexible workplace where you'll belong and be encouraged.
In? OCI ? AI Infrastructure ?org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. In this role, you will drive building state-of-the-art training infrastructure for massive GPU clusters, as well as designing agentic systems deployed on OCI infrastructure at enterprise-scale. You will be innovating on leading principles of agentic software development and driving the frontier on infrastructure that maximizes the potential of bleeding-edge GPU clusters.
We are working at the forefront of Generative AI (GenAI) landscape working with teams across Oracle on multi-modal data generation and leading the framework across Oracle.
Design and develop AI software in Java, Python, and other languages.?
Participate in the entire software lifecycle - development, testing, CI/CD and production operations
Participate in the entire model development cycle - training, fine-tuning, model serving, evaluation/benchmarking and human preference learning.
Apply engineering principles for defining robust and maintainable architectures and designs.?
Build cloud service on top of the modern Infrastructure as Service (IaaS) building blocks at OCI
Design and build distributed, scalable, fault tolerant software systems to facilitate development of GenAI models.
Identify requirements, scope solutions, estimate work, schedule deliverables. Help establish and drive the adoption of outstanding coding standards and patterns and help enhance our inclusive engineering culture.
Contribute to publications, blogs and open-source ML performance submissions partnering with product managers
Balance between product feature development and production operational concerns like ops automation, structured logging, instrumentation for metrics and participating in on-call.

View full posting on CareerOneStop → ID: 4b08e880772a

Machine Learning Engineering Manager

Indeed · Helena, MT

Manager Doctorate

2026-06-03

MT 2026-06-03

Responsibilities

At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
Work to understand, prioritize, and plan the team's work items without external guidance.
Ensure delivery of machine learning solutions, set expectations for what can be done and by when, and prioritize incoming projects.
Improve existing Agile, ML, and A/B testing processes and develop new ones.
Scope projects, gather and improve on requirements, and delegate work effectively.
Partner with and provide project direction and feedback to cross-functional peers, including Product Managers, Software Engineers.
Remove roadblocks and give individual contributors autonomy and ownership.
Brainstorm with teammates about practical experimental design, navigating production codebases, and model development.
Be prepared to closely engage and contribute directly to implementation when necessary.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with a minimum of 3 years experience
Demonstrated achievement as a Manager in Machine Learning Engineering, overseeing teams of 3 or more, and addressing intricate, large-scale problems
Well-versed in coding (Python, Java, Go, or C++) and experience with SQL Databases like Presto, and data processing frameworks like Spark
Have full-stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring
Highly effective in coaching Machine Learning Engineers, facilitating qualification enhancement, and fostering career development

View full posting on CareerOneStop → ID: 86c5ccbc5a93

Principal Machine Learning Engineer

Oracle · Helena, MT

Senior Master's

2026-06-03

MT 2026-06-03

Requirements

BS/MS in Computer Science or equivalent experience
6-10+ years building and shipping enterprise distributed or cloud-native systems
Experience scaling heterogeneous CPU/GPU training infrastructure for large multimodal frontier models
Strong foundation in system design, distributed systems, and cloud architecture best practices
Proficiency in Java, Python, or similar object-oriented languages
Experience building highly available services using service-oriented design patterns and service-to-service communication protocols
Proven ability to deliver impact in collaborative, fast-paced environments
Strong verbal and written communication skills, including technical design documentation
Hands-on experience with containers and orchestration technologies such as Kubernetes and Docke

Preferred

Production experience with Cloud and ML technologies
Experience working in the below areas and algorithms will be ideal but not mandatory:?
Generative AI Modeling: Customizing LLM's, build and deploy LLM's at scale for large scale data generation
Algorithms: Transformer models, Attention mechanism, Prompt tooling

Responsibilities

At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors. We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world.
Values are OCI's foundation and how we deliver excellence. We strive for equity, inclusion, and respect for all. We are committed to the greater good in our products and our actions. We are constantly learning and taking opportunities to grow our careers and ourselves. We challenge each other to stretch beyond our past to build our future.
You are the builder here. You will be part of a team of smart, motivated, and diverse people and given the autonomy and support to do your best work. It is a dynamic and flexible workplace where you'll belong and be encouraged.
In? OCI ? AI Infrastructure ?org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. In this role, you will drive building state-of-the-art training infrastructure for massive GPU clusters, as well as designing agentic systems deployed on OCI infrastructure at enterprise-scale. You will be innovating on leading principles of agentic software development and driving the frontier on infrastructure that maximizes the potential of bleeding-edge GPU clusters.
We are working at the forefront of Generative AI (GenAI) landscape working with teams across Oracle on multi-modal data generation and leading the framework across Oracle.
Design and develop AI software in Java, Python, and other languages.?
Participate in the entire software lifecycle - development, testing, CI/CD and production operations
Participate in the entire model development cycle - training, fine-tuning, model serving, evaluation/benchmarking and human preference learning.
Apply engineering principles for defining robust and maintainable architectures and designs.?
Build cloud service on top of the modern Infrastructure as Service (IaaS) building blocks at OCI
Design and build distributed, scalable, fault tolerant software systems to facilitate development of GenAI models.
Identify requirements, scope solutions, estimate work, schedule deliverables. Help establish and drive the adoption of outstanding coding standards and patterns and help enhance our inclusive engineering culture.
Contribute to publications, blogs and open-source ML performance submissions partnering with product managers
Balance between product feature development and production operational concerns like ops automation, structured logging, instrumentation for metrics and participating in on-call.

View full posting on CareerOneStop → ID: dd11225a881e

Senior Machine Learning Engineer

Indeed · Helena, MT

Senior Doctorate

2026-06-03

MT 2026-06-03

Responsibilities

As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to drive value and better customer experiences for our Sourcing product, which connects employers with new talent through AI. This Senior MLE will help us improve our automated outreach quality, building new agentic experiences, and LLMOps reliability and infrastructure.
Autonomously deliver ML and AI projects, including prompt development and evaluation, training ML models, building LLM-as-a-Judge capabilities, and building recommendation / ranking systems
Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our Sourcing product
Estimate potential business impact of AI and ML and balance tradeoffs between delivery velocity and systematic infrastructure investments
Collaborate with cross-functional partners, including Machine Learning Engineers, Data Scientists, Software Engineers, Product, and UX designers/researchers
Define and implement evaluation, observability, and production monitoring approaches for ML and LLM-based systems.
Serve as a trusted partner and communicator for cross-functional and cross-team counterparts, translating technical concepts to facilitate productive collaboration.
Mentor other Machine Learning Engineers, Data Scientists, and Software Engineers on the team
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 5 years of related experience; or a Master's degree with a minimum of 3 years of experience; or a PhD without experience
Prior success in deploying impactful Machine Learning and/or LLM-based solutions to large-scale production systems
Solid knowledge of data structures and algorithms
Demonstrated sense of ownership and accountability as a key contributor in the technical and product domains
Familiarity with agent orchestration frameworks, LLM observability tools, and prompt optimization techniques (e.g. GEPA)
Knowledge of and practical experience working on Deep Learning libraries (like Torch, Tensorflow, etc.) and modern ML/LLM tooling
Familiarity with modern ML system design, including evaluation, experimentation, and production monitoring for predictive and LLM-based systems
Excellent written and verbal communication, effective with technical and business audiences

View full posting on CareerOneStop → ID: c5d53fff4ef2

Associate Director, Data Science

Chewy Inc. · Bellevue, WA

Director Doctorate

2026-06-03

WA 2026-06-03

Requirements

Apply advanced mathematics and data science methodologies;
Standard machine learning and statistical techniques including predictive models (time series, regression, etc.), classification, forecasting; and

View full posting on CareerOneStop → ID: 78114146d8aa

Machine Learning Engineer

FlightSafety International Inc · Seattle, WA

Mid-level

2026-06-03

WA 2026-06-03

Preferred

Experience with distributed task queues or stateful workflow engines for managing complex, multi-step AI processes
Experience with frameworks designed for horizontal scaling of compute-intensive ML workloads
Experience designing "agent-loop" architectures that involve tool-use, self-correction, and multi-step reasoning
Familiarity with vector storage systems and high-throughput data processing pipelines
Wage Transparency
Pay for this position is based on a number of factors includi

Responsibilities

As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You will bridge the gap between core AI research and production-grade engineering, developing scalable platforms for autonomous agents, advanced retrieval systems, and automated model optimization.
This position is an individual contributor role reporting to the
Director, Machine Learning Engineering
*Responsibility
Build and maintain high-performance distributed systems to support large-scale model inference and data processing
Design frameworks for multi-agent systems, focusing on state management, reliability, and long-running autonomous workflows
Architect sophisticated Retrieval-Augmented Generation (RAG) pipelines and advanced context management strategies to improve model accuracy and relevance
Develop platform-level tools for automated prompt engineering, evaluation, and optimization to accelerate the AI development lifecycle
Implement robust ML pipelines, focusing on observability, versioning, and the seamless deployment of generative AI services
Job Designation
Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation)

View full posting on CareerOneStop → ID: 5af1e4f57cdd

Product Data Science Intern

FlightSafety International Inc · Seattle, WA

Intern Master's

2026-06-03

WA 2026-06-03

Responsibilities

Docusign's Product Data Science team is looking for a Data Scientist Intern to support the development of key data products and capabilities to enable data-driven product development and decision making. In this role, you would be part of the Product Data Science team and work directly in partnership with a variety of stakeholders including but not limited to Product, Engineering and User Experience partners to support and empower them with data-driven actionable insights. You will be embedded in specific product spaces requiring you to establish and grow relationships. As a Data Scientist Intern, you'll dig into the data to uncover insights, identify opportunities for product improvements and new product development, define product metrics with goals, design experiments and develop data science models to drive customer experience, engagement, and adoption of Docusign's products.
This role is not eligible for OPT or sponsorship now or in the future.
This position is an individual contributor role reporting to the Director, Product Data Science.
*Responsibility
Collaborate with cross-functional teams to research, build and improve data analysis to identify opportunities for product improvements, new product features, product utilization, and improve customer experience, engagement, and retention
Partner closely with the product managers, user researchers, engineers, and leadership to capture and prioritize potential insights, analysis, and data product opportunities that will drive maximum business impact
Leverage data to develop actionable analytical insights and present findings to senior management
Partner with Product teams to design, administer, and analyze the results of A/B and multivariate tests and other ML models
Design and build dashboards to provide actionable insights and key business metrics
Design, build and test reliable data pipelines to extract and transform data
Identify, design, and implement process improvements by automating manual processes for greater efficiency
Collaborate with stakeholders across organizations to support their data needs
Implement data quality checks to maintain the high quality of data
Optimize and maintain the existing pipelines
Document the work in confluence and Alation
Job Designation
*Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation)

View full posting on CareerOneStop → ID: 093d7411edef

Senior Staff Research Data Scientist, DevIE

Google · Kirkland, WA

Senior Doctorate

2026-06-03

WA 2026-06-03

Requirements

Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.

Preferred

12 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 10 years of work experience with a PhD degree.

Responsibilities

Our mission is to accelerate Google's velocity by empowering developers with AI-ready knowledge, trusted content, and scaled and targeted enablement programs.
We are looking for a Data Scientist (DS) who can work in a rapidly evolving tech landscape with novel methodologies, to generate actionable insights for product teams and leaders.
In this role, you will engage deeply with Google DeepMind and the core of Google's AI capabilities. You will shape the investigative directions and strategies for Gemini, revealing actionable insights into how it integrates with Google's complex software engineering ecosystem. Additionally, you will drive an understanding of how various agentic capabilities affect software and model development workflows, leveraging these insights to optimize complex systems at a Google scale.
The US base salary range for this full-time position is $262,000-$365,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 337abe52356b

Staff Machine Learning Engineer, AI Research

Cribl, Inc · Olympia, WA

Senior

2026-06-03

WA 2026-06-03

B2B SAAS data observability software. Join the company that's building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world's biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructur

View full posting on CareerOneStop → ID: 01e8c49272f2

AIML - Sr Machine Learning Engineer - Data and ML Innovation

Apple · Seattle, WA

Senior

2026-06-02

WA 2026-06-02

Requirements

Deep technical skills in one or more machine learning areas, such as computer vision, audio, combinatorial optimization, causality analysis, natural language processing, and deep learning.
Strong software development skills with proficiency in Python; hands-on experience working with deep learning toolkits like PyTorch, TensorFlow, or JAX (one of).
5+ years of experience developing and evaluating ML applications, demonstrating a passion for understanding and improving model/data quality.'

Preferred

Deep understanding of multi-modal foundation models.
Staying up-to-date with emerging trends in generative AI and multi-modal LLMs.
The ability to formulate machine learning problems, design, experiment, implement, and communicate solutions effectively with multi-functional teams.
Demonstrated publication records in relevant conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc.).
Track records of adopting ML to solve cross-disciplinary problems.

Responsibilities

Would you like to be a part of Apple's AI and Machine Learning org, where we encourage and create groundbreaking technology for multi-modal models with strong agent and reasoning capabilities? The Data and Machine Learning Innovation (DMLI) team is seeking a passionate Machine Learning Engineer to explore new methods, challenge existing metrics and protocols, and develop new insightful practices for real-world ML challenges. As a team member, you will work on some of the most ambitious technical challenges in the field. Your role will involve collaborating closely with our team of machine learning researchers, engineers, and data scientists. Together, you will spearhead groundbreaking research initiatives and develop transformative products designed to build for billions of users worldwide.
As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying innovative research in foundation models to with a particular focus on audio data. This includes working across the full ML pipeline-from pre-training on large-scale unlabeled audio corpora to post-training evaluation and fine-tuning with task-specific datasets. The solutions you develop will have a significant impact on future Apple software and hardware products, as well as the broader ML ecosystem.
Your responsibilities will extend to designing and developing a comprehensive multi-modal data generation and curation framework for foundation models at Apple. You will also contribute to building robust model evaluation pipelines that support continuous improvement and performance assessment. In addition, the role involves analyzing multi-modal data to better understand its influence on model behavior and outcomes. Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues.
YOUR WORK MAY SPAN VARIOUS APPLICATIONS, INCLUDING:
Designing self-supervised and semi-supervised representation learning pipelines, and fine-tuning strategies for tasks like speech recognition and speaker identification.
Applying data selection techniques such as novelty detection and active learning across multi modalities to improve data efficiency and reduce distributional gaps.
Modeling data distributions using ML/statistical methods to uncover patterns, reduce redundancy, and handle out-of-distribution challenges.
Rapidly learning new methods and domains as needed, and guiding product teams in selecting effective ML solutions.

View full posting on CareerOneStop → ID: c4f2db14d2d3

Chief Data Scientist - AI Safety

Pacific Northwest National Laboratory · Seattle, WA

Director Doctorate

2026-06-02

WA 2026-06-02

Requirements

Based in Richland, WA or Seattle, WA with onsite presence required
Clearance required (see below for details)
Travel may be required for stakeholder engagement, project events, and sponsor reviews.
BS/BA and 9+ years of relevant work experience -OR-
MS/MA and 7+ years of relevant work experience -OR-
PhD with 5+ year of relevant experience
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Advanced degree in computer science, engineering, data science, mathematics, or a related discipline.
Active DOE Q or TS/SCI clearance and ability to maintain such clearance.
Demonstrated impact in AI Safety (e.g., peer-reviewed publications, recognized awards, contributions to community standards).
National reputation in AI Safety, frontier model evaluation, trustworthy AI, secure machine learning operations, or related mission relevant technical areas.
Familiarity with agentic AI safety (tool-use governance, retrieval hygiene, autonomous decision workflows) and evaluation of multi-step reasoning systems.
Experience developing and applying cutting edge AI/ML in national security environments, with an understanding of mission needs and operational constraints.
Experience serving as PI or project manager on multi-institution R&D efforts.
Strong record of securing external funding, managing research portfolios, and initiating new R&D programs in applied AI or AI Safety domains.
Experience working with sponsors such as DOE, NNSA, DoD, DHS, or other mission agencies, with the ability to help shape strategic research investments.
Proven ability to communicate complex technical concepts to diverse audiences across government, industry, and academia.

Responsibilities

Our AI & Data Analytics division is seeking a Chief Data Scientist with deep expertise in data science and experience in AI Safety for national security missions. The selected candidate will lead large, multi-year research and development programs within the AI and Data Analytics Division, which includes over 400 staff specializing in data science, applied mathematics, advanced analytic architectures, software engineering, and human-centered computing. We support PNNL's mission by contributing to impactful, mission-focused applied R&D projects that help tackle national security challenges. This role requires deep technical expertise and the ability to translate emerging research into mission-ready capabilities
The Chief Data Scientist will shape national technical direction, engage directly with sponsors and senior leadership, and serve as a strategic partner in aligning PNNL's AI safety portfolio with evolving mission and policy requirements. This individual will guide technical direction, mentor interdisciplinary teams, and collaborate closely with software engineers to transition cutting edge research into field-ready capabilities. In addition to leading research efforts, the Chief Data Scientist will serve as a key interface with sponsors and stakeholders, leveraging domain expertise to align PNNL's research agenda with evolving mission requirements.
The chosen candidate will have the unique opportunity to drive real-world impact at mission tempo while supporting PNNL's mission to tackle grand challenges through science, technology, and innovation. Key responsibilities will include:
Strategic Leadership and Vision:
Shape and execute forward-looking strategies for advancing AI Safety research, evaluation methodologies, and trustworthy deployment practices within PNNL's national security mission space.
Partner with government sponsors as a senior technical leader, translating evolving mission priorities and operational risk considerations into actionable research direction and investment opportunities.
Lead high-visibility proposal development to help shape national investment in frontier-model safety, agentic AI governance, secure machine learning operations, and evaluation infrastructure.
Scientific and Technical Leadership:
Lead nationally visible AI Safety programs, ensuring technical excellence, sponsor alignment, risk-informed execution, and timely delivery of impactful results.
Serve as a senior technical leader in AI Safety, guiding approaches for evaluating, testing, and characterizing the behavior, risks, and emergent properties of AI models including but not limited to large language models, multimodal models, and agentic AI systems.
Provide technical leadership that supports interdisciplinary teams, helping shape research methodologies, data science and engineering best practices, and evaluation strategies while overseeing end-to-end analytic workflows.
Build and sustain collaborations across DOE laboratories, federal agencies, academia, and industry to accelerate innovation and deliver integrated, mission-aligned AI Safety capabilities.
Partner with software engineering and operational teams to transition research outputs into secure, scalable real-world systems that support national security missions.
External Influence & National Representation:
Represent PNNL as a senior AI Safety expert in technical exchanges, working groups, and high-impact national and international forums.
Publish influential research, contribute to emerging standards, and help shape national discourse on AI Safety.
Communicate PNNL's AI capabilities and mission relevance to external stakeholders, articulating use cases, technical solutions, and emerging challenges within the broader national security landscape.
Mentorship & Workforce Development:
Support the technical and professional development of junior through senior researchers, offering guidance on research challenges, technical leadership skills, and effective collaboration practices.
Contribute to an inclusive and learning-oriented environment that encourages scientific rigor, safety-first innovation, and high-impact interdisciplinary work.
Collaborate with other senior researchers to strengthen PNNL's AI Safety workforce through mentorship, knowledge sharing, and community building.
*Read more about the AIDA division! (https://www.pnnl.gov/ai-and-data-analytics)

View full posting on CareerOneStop → ID: 96cc105ee0f6

Senior Machine Learning Engineer, Machine Learning Platform Technologies

Apple · Seattle, WA

Senior Bachelor's

2026-06-02

WA 2026-06-02

Requirements

Bachelor's degree or higher in Computer Science or related technical field.
5 year+ industry experience in distributed system and ML Modeling (Search, Recommendation, NLP, Ads, Statistics).
Experience with high throughput services particularly at supercomputing scale.
Proficient with running applications on Cloud (AWS / Azure or equivalent) using Kubernetes, Docker etc.
Proficient in building and maintaining systems written in modern languages (eg: Golang, Rust, Python)

Preferred

Familiar with GenAI Applications and popular agentic framework like Langchain and Langgraph
Familiar with embedding model and llm serving like Nvidia TensorRT-LLM, vLLLM, DeepSpeed, Nvidia Triton Server etc.
Familiar with very large scale serving system

Responsibilities

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
At Apple, imagination and ambition come together to shape what's next. Every product we build, every service we design, and every experience we deliver is born from collaboration-making each other's ideas stronger and more impactful. We believe in thinking differently, challenging the status quo, and pushing the boundaries of technology and intelligence to create products that bring joy and change lives for the better. Our strength comes from the diversity of our people and perspectives, and when everyone is included, we do the best work of our lives. If you're bold, curious, and passionate about building best-in-class technology, Apple is the place to not just join something-but to add something.
As part of this group, you will develop GenAI search and recommendation application end to end and partner with a lot of engineering teams across Apple.
The Partner Adoption team, part of the Machine Learning Platform Technologies organization, is the backbone of onboarding applications to Apple's world-class search and recommendation platform. In this role, you'll work end-to-end on feature and product design across a broad range of Apple services-including Apple Music, TV+, App Store, Books, Games, Podcasts, Siri, and more. As a key member of the team, you'll design and build large-scale server-side functionality while also exploring and delivering cutting-edge GenAI applications and features powered by large language models. You'll partner closely with product, platform, and design teams to bring innovations to life-reaching millions, and even billions, of users worldwide with the reliability and excellence Apple is known for.

View full posting on CareerOneStop → ID: 5016dea3e918

Chief Data Scientist - AI Safety

Pacific Northwest National Laboratory · Richland, WA

Director Doctorate

2026-06-02

WA 2026-06-02

Requirements

Based in Richland, WA or Seattle, WA with onsite presence required
Clearance required (see below for details)
Travel may be required for stakeholder engagement, project events, and sponsor reviews.
BS/BA and 9+ years of relevant work experience -OR-
MS/MA and 7+ years of relevant work experience -OR-
PhD with 5+ year of relevant experience
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Advanced degree in computer science, engineering, data science, mathematics, or a related discipline.
Active DOE Q or TS/SCI clearance and ability to maintain such clearance.
Demonstrated impact in AI Safety (e.g., peer-reviewed publications, recognized awards, contributions to community standards).
National reputation in AI Safety, frontier model evaluation, trustworthy AI, secure machine learning operations, or related mission relevant technical areas.
Familiarity with agentic AI safety (tool-use governance, retrieval hygiene, autonomous decision workflows) and evaluation of multi-step reasoning systems.
Experience developing and applying cutting edge AI/ML in national security environments, with an understanding of mission needs and operational constraints.
Experience serving as PI or project manager on multi-institution R&D efforts.
Strong record of securing external funding, managing research portfolios, and initiating new R&D programs in applied AI or AI Safety domains.
Experience working with sponsors such as DOE, NNSA, DoD, DHS, or other mission agencies, with the ability to help shape strategic research investments.
Proven ability to communicate complex technical concepts to diverse audiences across government, industry, and academia.

Responsibilities

Our AI & Data Analytics division is seeking a Chief Data Scientist with deep expertise in data science and experience in AI Safety for national security missions. The selected candidate will lead large, multi-year research and development programs within the AI and Data Analytics Division, which includes over 400 staff specializing in data science, applied mathematics, advanced analytic architectures, software engineering, and human-centered computing. We support PNNL's mission by contributing to impactful, mission-focused applied R&D projects that help tackle national security challenges. This role requires deep technical expertise and the ability to translate emerging research into mission-ready capabilities
The Chief Data Scientist will shape national technical direction, engage directly with sponsors and senior leadership, and serve as a strategic partner in aligning PNNL's AI safety portfolio with evolving mission and policy requirements. This individual will guide technical direction, mentor interdisciplinary teams, and collaborate closely with software engineers to transition cutting edge research into field-ready capabilities. In addition to leading research efforts, the Chief Data Scientist will serve as a key interface with sponsors and stakeholders, leveraging domain expertise to align PNNL's research agenda with evolving mission requirements.
The chosen candidate will have the unique opportunity to drive real-world impact at mission tempo while supporting PNNL's mission to tackle grand challenges through science, technology, and innovation. Key responsibilities will include:
Strategic Leadership and Vision:
Shape and execute forward-looking strategies for advancing AI Safety research, evaluation methodologies, and trustworthy deployment practices within PNNL's national security mission space.
Partner with government sponsors as a senior technical leader, translating evolving mission priorities and operational risk considerations into actionable research direction and investment opportunities.
Lead high-visibility proposal development to help shape national investment in frontier-model safety, agentic AI governance, secure machine learning operations, and evaluation infrastructure.
Scientific and Technical Leadership:
Lead nationally visible AI Safety programs, ensuring technical excellence, sponsor alignment, risk-informed execution, and timely delivery of impactful results.
Serve as a senior technical leader in AI Safety, guiding approaches for evaluating, testing, and characterizing the behavior, risks, and emergent properties of AI models including but not limited to large language models, multimodal models, and agentic AI systems.
Provide technical leadership that supports interdisciplinary teams, helping shape research methodologies, data science and engineering best practices, and evaluation strategies while overseeing end-to-end analytic workflows.
Build and sustain collaborations across DOE laboratories, federal agencies, academia, and industry to accelerate innovation and deliver integrated, mission-aligned AI Safety capabilities.
Partner with software engineering and operational teams to transition research outputs into secure, scalable real-world systems that support national security missions.
External Influence & National Representation:
Represent PNNL as a senior AI Safety expert in technical exchanges, working groups, and high-impact national and international forums.
Publish influential research, contribute to emerging standards, and help shape national discourse on AI Safety.
Communicate PNNL's AI capabilities and mission relevance to external stakeholders, articulating use cases, technical solutions, and emerging challenges within the broader national security landscape.
Mentorship & Workforce Development:
Support the technical and professional development of junior through senior researchers, offering guidance on research challenges, technical leadership skills, and effective collaboration practices.
Contribute to an inclusive and learning-oriented environment that encourages scientific rigor, safety-first innovation, and high-impact interdisciplinary work.
Collaborate with other senior researchers to strengthen PNNL's AI Safety workforce through mentorship, knowledge sharing, and community building.
*Read more about the AIDA division! (https://www.pnnl.gov/ai-and-data-analytics)

View full posting on CareerOneStop → ID: efac35705ba0

Data Scientist

iSpot.tv, INC. · Bellevue, WA

Mid-level Master's

2026-06-02

WA 2026-06-02

Implement industry-standard predictive modeling solutions. Analyze, manipulate, clean, and process large and messy data using predictive modeling solutions and cloud-based computing resources/infrastructure to scale and optimize data science tools and pipelines. Code original R/Python scripts, optim

View full posting on CareerOneStop → ID: 3c086ed88f3e

Data Scientist, PPE Product Intelligence

Amazon · Seattle, WA

Mid-level Bachelor's

2026-06-02

WA 2026-06-02

Requirements

1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
Bachelor's degree

Preferred

Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)

Responsibilities

Design and run rigorous experiments at scale to evaluate and improve foundation model performance across hundreds of millions of products, geographies, and business verticals
Lead the end-to-end lifecycle of evaluation models - from research and experimentation through production launch - including defining success metrics, obtaining stakeholder sign-off, and managing rollout
Conduct online and offline labs to measure the real-world impact of model improvements beyond accuracy, including downstream supply chain, inventory, and financial outcomes
Develop and deploy production-grade statistical models using Python, Scala, SQL, and related tools
Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform model development
Translate complex research findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
No two days look the same, but most will involve some combination of deep technical work, cross-functional collaboration, and scientific thinking at a scale you won't find anywhere else.
You might start the morning reviewing the results of an experiment running across hundreds of millions of products - analyzing whether a new foundation model variant is improving generalization on cold-start items, or whether a novel data generation approach is meaningfully shifting forecast quality. You'll dig into the numbers, form a hypothesis, and design the next iteration.
Later in the day, you could be in a stakeholder review, walking business and engineering partners through a set of launch metrics - explaining not just forecast accuracy, but the downstream supply chain and financial impact your model is driving. Getting a model to production at Amazon requires rigor: you'll define success criteria, run online and offline labs to validate real-world impact, and build the case for sign-off across technical and business stakeholders.
You'll write code - Python, Scala, SQL - to process and analyze data at a scale most scientists never encounter. You'll collaborate closely with scientists, engineers, and business teams, and contribute to research that has a real chance of being published and advancing the field.

View full posting on CareerOneStop → ID: 076ebf6dc450

Director, Marketing Data Science

Meta · Seattle, WA

Director Doctorate

2026-06-02

WA 2026-06-02

Requirements

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience, Master's degree preferred
10+ years of work experience in data science or decision science (or 8+ years experience with a Ph.D.) supporting a Marketing function
Advanced experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and statistical/mathematical software (e.g. R)
Experience leading the building of statistical/computational tools in support of marketing functions
Advanced knowledge of marketing analytics, survey design, and statistical methods
Very comfortable personally using AI tools and transforming organizations to be AI-Native
Strong leadership skills, with the ability to operate autonomously and manage cross-functional teams
Excellent stakeholder management and communication skills, with experience presenting to executive leadership

Preferred

Previous experience in Public Affairs Marketing or Public Opinion Polling
3+ years in Corporate Communications Analytics (e.g. social listening)
Expertise in high-frequency measurement models, campaign optimization, and real-time reporting

Responsibilities

We are seeking a highly experienced Senior Marketing Data Science Leader to drive measurement, analytics, and strategy across Corporate, Public Affairs, AI Marketing and Corporate Communications at Meta. This role is pivotal in supporting high-impact marketing campaigns, developing innovative measurement frameworks, and collaborating with executive leadership to optimize marketing effectiveness.
Lead Measurement & Analytics: Oversee the measurement of campaigns, including AI Marketing, Corporate Marketing, and Public Affairs. Develop and refine high-frequency measurement models for real-time campaign optimization and reporting.
Strategic Campaign Support: Partner with VPs and Directors to design, execute, and evaluate marketing campaigns across multiple regions and business units. Lead the development of holdout strategies and funnel analysis to validate campaign effectiveness.
Innovation & Efficiency: Invent and implement new measurement programs to consolidate trackers, enhance efficiency, and optimize resource allocation.
Cross-Functional Leadership: Operate with autonomy, managing a team of ~15 and collaborating with cross-functional partners in Product, Research, and Corporate Marketing. Support recruiting and interview process improvements for Marketing Data Science.
Stakeholder Engagement: Serve as a direct report to the VP, Marketing Data Science, and engage with peers at the Director level. Present findings and recommendations to senior leadership, influencing strategic decisions.
Community & Thought Leadership: Amplify the impact of Meta's Analytics community through blog contributions, paid media strategies, and recruiting initiatives.

View full posting on CareerOneStop → ID: 745721090f79

Director, Marketing Data Science

Meta · Bellevue, WA

Director

2026-06-02

WA 2026-06-02

Requirements

Advanced experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and statistical/mathematical software (e.g. R)
Very comfortable personally using AI tools and transforming organizations to be AI-Native
Strong leadership skills, with the ability to operate autonomously and manage cross-functional teams
Excellent stakeholder management and communication skills, with experience presenting to executive leadership

Preferred

Previous experience in Public Affairs Marketing or Public Opinion Polling
3+ years in Corporate Communications Analytics (e.g. social listening)
Expertise in high-frequency measurement models, campaign optimization, and real-time reporting

Responsibilities

We are seeking a highly experienced Senior Marketing Data Science Leader to drive measurement, analytics, and strategy across Corporate, Public Affairs, AI Marketing and Corporate Communications at Meta. This role is pivotal in supporting high-impact marketing campaigns, developing innovative measurement frameworks, and collaborating with executive leadership to optimize marketing effectiveness.
Lead Measurement & Analytics: Oversee the measurement of campaigns, including AI Marketing, Corporate Marketing, and Public Affairs. Develop and refine high-frequency measurement models for real-time campaign optimization and reporting.
Strategic Campaign Support: Partner with VPs and Directors to design, execute, and evaluate marketing campaigns across multiple regions and business units. Lead the development of holdout strategies and funnel analysis to validate campaign effectiveness.
Innovation & Efficiency: Invent and implement new measurement programs to consolidate trackers, enhance efficiency, and optimize resource allocation.
Cross-Functional Leadership: Operate with autonomy, managing a team of ~15 and collaborating with cross-functional partners in Product, Research, and Corporate Marketing. Support recruiting and interview process improvements for Marketing Data Science.
Stakeholder Engagement: Serve as a direct report to the VP, Marketing Data Science, and engage with peers at the Director level. Present findings and recommendations to senior leadership, influencing strategic decisions.
Community & Thought Leadership: Amplify the impact of Meta's Analytics community through blog contributions, paid media strategies, and recruiting initiatives.

View full posting on CareerOneStop → ID: 93f4a2aa0221

Machine Learning Engineer, Monetization Engineering

Pinterest, Inc. · Seattle, WA

Mid-level

2026-06-02

WA 2026-06-02

Requirements

2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
Degree in computer science, machine learning, statistics, or related field
End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems

Preferred

Publications at top ML conferences
Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
Expertise in scalable realtime systems that process stream data
Passion for applied ML and the Pinterest product
Background in computational advertising

Responsibilities

Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
Work in a high-impact environment with quick experimentation and product launches
Keep up with industry trends in recommendation systems
Leverage LLMs to enhance content understanding

View full posting on CareerOneStop → ID: 665557491c00

Sr. Machine Learning Engineer, Monetization Engineering

Pinterest, Inc. · Seattle, WA

Senior Doctorate

2026-06-02

WA 2026-06-02

Requirements

2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
Degree in computer science, statistics, or related field; or equivalent experience
End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems

Preferred

M.S. or PhD in Machine Learning or related areas
Publications at top ML conferences
Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
Expertise in scalable realtime systems that process stream data
Passion for applied ML and the Pinterest product
Background in computational advertising
*Relocation Sta

Responsibilities

Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
Work in a high-impact environment with quick experimentation and product launches
Keep up with industry trends in recommendation systems
Leverage LLMs to enhance content understanding

View full posting on CareerOneStop → ID: e988897a3dc6

Staff Machine Learning Engineer, Ads Conversion

Pinterest, Inc. · Seattle, WA

Senior

2026-06-02

WA 2026-06-02

Requirements

Degree in Computer Science, Statistics, or a related field.
6+ years of industry experience building production ML systems at scale (Search, Recommendations, or Ranking).
2+ years of experience leading technical projects or teams.
Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.
Experience with Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.
Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.
High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final deliverables.
Strong mathematical foundation and experience with statistical methods and A/B testing.
We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
This role will need to be in the office for in-person collaboration 1-2 times every 6 months and therefore can be situated anywhere in the country.
This role will need to be in the office for in-person collaboration 1-2 times every 6 months and

Responsibilities

Lead the technical direction and development of state-of-the-art applied ML projects for ads conversion.
Design and build large-scale DNN models to improve user action prediction with low latency.
Mine text, visual, and user signals to better understand intention and infer interests from online activity.
Use AI to accelerate analysis and iteration, while applying judgment and verification to ensure correctness and quality.
Automate repeatable tasks such as documentation, reporting, and QA checks to speed up the development lifecycle.
Coach and mentor engineers while collaborating with product and sales to design new ad products.

View full posting on CareerOneStop → ID: 8665a4366393

Principal Data Scientist (AI Agent/Agentic)

Visa Usa Inc · Bellevue, WA

Senior

2026-06-01

WA 2026-06-01

Responsibilities

We are looking for a versatile, curious, and energetic Principal Data Scientist to join our team of passionate and dedicated engineers. We are the backbone for innovative data science and artificial intelligence developments at Visa and we thrive on solving complex challenges on a global scale! As a Principal Data Scientist, you will be an integral part of a multi-functional development team inventing, designing, building, and testing products that reach a truly global customer base.
You will face big challenges and question the status quo, changing the way data products are developed at Visa! Come join us and see your efforts shape the digital future of payments.
The focus is on defining, executing, and delivering product and technical features at scale quickly and promoting a diverse culture of cross-functional collaboration and engineering excellence. Be an idea leader and bring industry best practices to benefit the team and the wider organization. The ability to balance demanding business capabilities with building for operational excellence while meeting regulatory, security and privacy requirements.
Ability to quickly grasp and evaluate new ideas and technologies from internal and external sources. Lead/Influence multiple teams, matching them with appropriate technology and business problems while building a culture of both innovation and drive for excellence.
Transform our digital offerings by leveraging AI to enhance our current product line and develop exciting new products targeting our banking, fintech and integration partners, which will enable the next wave of innovation in payments. We need a strong technology leader, who is an expert in data science, agile delivery, building purpose driven teams, and has a background in complex integration projects. Prior experience in payments, or a background in building high volume transaction and data processing systems is preferred.
The successful candidate will be comfortable navigating the challenging dynamic payments space and leading global teams responsible for platform transformation efforts. This candidate will play a pivotal role in our continued embrace of AI, seeking new paths to revenue by improving delivery efficiency and pushing forward for new products.
Provides technical expertise and mentors others to implement extensible, maintainable, and reusable code, defines framework, principles, coding patterns, guidelines, styles, and standard methodologies, and adheres to all security requirements for the application of artificial intelligence and data science.
Develops strategies for and leads team's efforts to drive efficiencies across data extraction and ensure data quality and completeness using data wrangling, complex data modeling, and artificial intelligence.
Ensures adherence to data management principles, governance, process, and tools to maintain data quality across products.
Advises on technical specifications during discussions with collaborators (e.g., Product owners, business partners, Cybersecurity) to identify and clarify sophisticated technical or business requirements and identify business needs and upstream and/or downstream system/application dependencies.

View full posting on CareerOneStop → ID: f58c6dd4b150

Sr Machine Learning Engineer, AI Research

Cribl, Inc · Olympia, WA

Senior

2026-06-01

WA 2026-06-01

B2B SAAS data observability software. Join the company that's building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world's biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructur

View full posting on CareerOneStop → ID: bbb5720d927f

Consultant - Data Science / Data Lake

Deloitte · Seattle, WA

Mid-level Bachelor's

2026-05-31

WA 2026-05-31

Requirements

2+ years of experience in analytics consulting, cybersecurity analytics, security operations, or a combination of these (including internships and in-school experience)
1+ years of experience with artificial intelligence development tools or frameworks such as vector databases, LangChain, or CrewAI
1+ years of experience using Python, Structured Query Language (SQL), R, or SAS to prepare data for analysis, engineer features, visualize data, or support machine learning workflows
Experience working with cybersecurity cloud platforms such as Google SecOps, Amazon Web Services (AWS), or Microsoft Azure, and exposure to security operations center (SOC) threat hunting or incident response
Bachelor's degree in Engineering, Mathematics, Statistics, Computer Science, Cybersecurity, or a field aligned to the role; or 4 years of equivalent professional experience
Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
Limited immigration sponsorship may be available.

Preferred

Experience supporting the design, development, or deployment of enterprise data science or artificial intelligence solutions
Experience applying artificial intelligence, machine learning, or advanced data engineering to cybersecurity use cases such as detection engineering or threat response support
Experience parsing and normalizing cyber or information technology telemetry datasets
Experience with PyTorch, Keras, TensorFlow, Scikit-learn, NumPy, or SciPy
Experience with Apache Kafka, Storm, or Spark
Experience creating client-ready materials using Microsoft PowerPoint or Microsoft Visio
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is .
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: 3541197cdfca

Data Scientist, PPE Product Intelligence

Amazon · Seattle, WA

Mid-level

2026-05-31

WA 2026-05-31

Requirements

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data scientist experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Experience applying theoretical models in an applied environment

Preferred

Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company

Responsibilities

Design and run rigorous experiments at scale to evaluate and improve foundation model performance across hundreds of millions of products, geographies, and business verticals
Lead the end-to-end lifecycle of evaluation models - from research and experimentation through production launch - including defining success metrics, obtaining stakeholder sign-off, and managing rollout
Conduct online and offline labs to measure the real-world impact of model improvements beyond accuracy, including downstream supply chain, inventory, and financial outcomes
Develop and deploy production-grade statistical models using Python, Scala, SQL, and related tools
Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform model development
Translate complex research findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
No two days look the same, but most will involve some combination of deep technical work, cross-functional collaboration, and scientific thinking at a scale you won't find anywhere else.
You might start the morning reviewing the results of an experiment running across hundreds of millions of products - analyzing whether a new foundation model variant is improving generalization on cold-start items, or whether a novel data generation approach is meaningfully shifting forecast quality. You'll dig into the numbers, form a hypothesis, and design the next iteration.
Later in the day, you could be in a stakeholder review, walking business and engineering partners through a set of launch metrics - explaining not just forecast accuracy, but the downstream supply chain and financial impact your model is driving. Getting a model to production at Amazon requires rigor: you'll define success criteria, run online and offline labs to validate real-world impact, and build the case for sign-off across technical and business stakeholders.
You'll write code - Python, Scala, SQL - to process and analyze data at a scale most scientists never encounter. You'll collaborate closely with scientists, engineers, and business teams, and contribute to research that has a real chance of being published and advancing the field.
The work is hard, the problems are unsolved, and the impact is immediate. If you want to do research that ships - this is where you do it.

View full posting on CareerOneStop → ID: 9904844c860a

Sr. Data Scientist, Enterprise Security Products

Amazon · Seattle, WA

Senior

2026-05-31

WA 2026-05-31

Requirements

6+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
5+ years of data scientist experience
Experience with statistical models e.g. multinomial logistic regression

Preferred

2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
Experience managing data pipelines
Experience as a leader and mentor on a data science team
Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)

Responsibilities

Build the intelligence behind AI-first security products: Design, train, and ship ML models that power agentic systems, anomaly detection, threat classification, and automated response - all running across multi-cloud environments.
Own the full science lifecycle: From problem framing and data exploration through model development, evaluation, production deployment, and monitoring. You build it, you ship it, you run it.
Build with AI to build AI: Use agentic coding tools, LLM-powered workflows, and experimental AI tooling to accelerate every phase of your work; from EDA to feature engineering to model iteration. Multiply your velocity and raise the bar for what one scientist can deliver.
Power agentic architectures: Develop the models, embeddings, RAG pipelines, evaluation frameworks, and feedback loops that make multi-agent security systems smart, safe, and customer-ready.
Prototype rapidly and validate with customers: Turn hypotheses into prototypes in days, not quarters. Iterate based on real customer signal and ship what works.
Partner across disciplines: Work directly with SDEs, applied scientists, security researchers, PMs, and UX designers to turn ambiguous problems into shipped solutions. Small team means short lines between you and the decision.
Communicate with impact: Translate complex modeling results into clear recommendations for engineers, product leaders, and senior executives. Influence direction with data.
Raise the science bar: Contribute to technical and science reviews, mentor teammates, and champion AI-first development practices. Help shape the science culture of a fast-growing team from the ground floor.
No two days look the same on this fast-growing, AI-first team. You might start your morning reviewing evaluation results from overnight model training runs, then dive into building a RAG pipeline or tuning a multi-agent orchestration loop. Before lunch, you're pair-prompting with an agentic coding assistant to stand up a new feature pipeline. In the afternoon, you join a design session with senior and principal scientists and engineers where your ideas carry weight regardless of title. You own science problems end to end, ship using the latest AI-assisted workflows, and see your models reach production fast. This is where builders thrive.

View full posting on CareerOneStop → ID: 988b33082669

Technical Project Manager - Machine Learning & Data Science

Cadmus · Olympia, WA

Manager Bachelor's

2026-05-30

WA 2026-05-30

Requirements

5+ years of experience as a Technical Project Manager or Scrum Master, managing cross-functional projects.
Bachelor's degree in Information Systems, BI or Analytics or Engineering.
Strong technical proficiency and experience working with Machine Learning (ML) or Data Science/Artificial Intelligence (DS/AI) teams.
Experience managing large, ambiguous, cross-functional programs operating in fast-paced, highly collaborative environments.
Experience performing TPM best practices (e.g., schedule development and tracking, risk management, status reporting).
Experience regularly maintaining and reporting program data, preferably in Jira.
Deep understanding of Agile and SDLC methodologies and leading/modeling process adherence.
Excellent communication and problem-solving skills.
Ability to facilitate teams and individuals working collaboratively and efficiently.
A composed presence, business acumen, and ability to communicate at multiple levels of the organization.
Experience with automation and/or AI tools such as ChatGPT, Gemini, etc.
Preferred certifications: PMP or Scrum Master.
*Additional Information:
Candidates must be eligible to work in the United States as a U.S Perm Resident or U.S. Citizen.

Responsibilities

Manage and coordinate across multiple engineering teams delivering Machine Learning (ML) and Data Science/Artificial Intelligence (DS/AI) features and capabilities to support the broader vision, goals, and objectives of the company. Coordinate activities with internal teams and external partners.
Oversee end-to-end activities to ensure coordination and on-time delivery. Build integrated schedules based on an understanding team's activities and interdependencies between teams. Manage removing blockers, risks, and issues. Report program status.
Lead Agile ceremonies and assist with story definition, backlog prioritization, and dependency resolution.
Help Engineering teams balance scope, timeline, and quality to achieve optimal outcomes based on an understanding of priorities.
Advocate for clear priorities, technical excellence, process and best practices adherence, and customer-focused outcomes.
Influence without authority and drive consensus across diverse stakeholders.

View full posting on CareerOneStop → ID: 9a2c5d789c8e

Data Scientist

Deloitte · Portland, OR

Mid-level Doctorate

2026-05-30

WA 2026-05-30

Requirements

Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
5+ Years of Experience in a Data Science or Machine Learning role.
5+ Years of Experience Proficiency in programming languages such as Python or R.
5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
5+ Years of Experience with data manipulation and analysis libraries like pandas and NumPy
Limited immigration sponsorship may be available
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Master's or Ph.D. in a relevant field.
Experience with big data technologies like Spark or Hadoop.
Experience with deep learning frameworks like TensorFlow or PyTorch.
Familiarity with cloud platforms such as AWS, Azure, or GCP.
Experience with data visualization tools like Tableau or Power BI.
Analytical/ Decision Making Responsibilities
Analytical ability to manage multiple projects and prioritize tasks into manageable work products
Can operate independently or with minimum supervision
Excellent Written and Communication Skills
Ability to deliver technical demonstrations
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400-207,800
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Responsibilities

Work with stakeholders to identify business problems and formulate them as data science challenges.
Collect, clean, and explore large datasets to uncover trends and patterns.
Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
Validate and deploy models into production environments.
Communicate findings and insights to technical and non-technical audiences through data visualization and presentations.
Stay up to date with the latest trends and technologies in data science and machine learning.
Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeano
Ability to meet deadlines
Ability to provide clear guidance to others
Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.

View full posting on CareerOneStop → ID: fb47222db27e

Data Scientist

Deloitte · Seattle, WA

Mid-level Doctorate

2026-05-30

WA 2026-05-30

Requirements

Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
5+ Years of Experience in a Data Science or Machine Learning role.
5+ Years of Experience Proficiency in programming languages such as Python or R.
5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
5+ Years of Experience with data manipulation and analysis libraries like pandas and NumPy
Limited immigration sponsorship may be available
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Master's or Ph.D. in a relevant field.
Experience with big data technologies like Spark or Hadoop.
Experience with deep learning frameworks like TensorFlow or PyTorch.
Familiarity with cloud platforms such as AWS, Azure, or GCP.
Experience with data visualization tools like Tableau or Power BI.
Analytical/ Decision Making Responsibilities
Analytical ability to manage multiple projects and prioritize tasks into manageable work products
Can operate independently or with minimum supervision
Excellent Written and Communication Skills
Ability to deliver technical demonstrations
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400-207,800
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Responsibilities

Work with stakeholders to identify business problems and formulate them as data science challenges.
Collect, clean, and explore large datasets to uncover trends and patterns.
Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
Validate and deploy models into production environments.
Communicate findings and insights to technical and non-technical audiences through data visualization and presentations.
Stay up to date with the latest trends and technologies in data science and machine learning.
Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeano
Ability to meet deadlines
Ability to provide clear guidance to others
Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.

View full posting on CareerOneStop → ID: 40c16c089c03

Data Scientist

Deloitte · Bellevue, WA

Mid-level Doctorate

2026-05-30

WA 2026-05-30

Requirements

Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
5+ Years of Experience in a Data Science or Machine Learning role.
5+ Years of Experience Proficiency in programming languages such as Python or R.
5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
5+ Years of Experience with data manipulation and analysis libraries like pandas and NumPy
Limited immigration sponsorship may be available
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Master's or Ph.D. in a relevant field.
Experience with big data technologies like Spark or Hadoop.
Experience with deep learning frameworks like TensorFlow or PyTorch.
Familiarity with cloud platforms such as AWS, Azure, or GCP.
Experience with data visualization tools like Tableau or Power BI.
Analytical/ Decision Making Responsibilities
Analytical ability to manage multiple projects and prioritize tasks into manageable work products
Can operate independently or with minimum supervision
Excellent Written and Communication Skills
Ability to deliver technical demonstrations
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400-207,800
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Responsibilities

Work with stakeholders to identify business problems and formulate them as data science challenges.
Collect, clean, and explore large datasets to uncover trends and patterns.
Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
Validate and deploy models into production environments.
Communicate findings and insights to technical and non-technical audiences through data visualization and presentations.
Stay up to date with the latest trends and technologies in data science and machine learning.
Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeano
Ability to meet deadlines
Ability to provide clear guidance to others
Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.

View full posting on CareerOneStop → ID: b2b19730a972

Finance Manager, Advertising Finance - Measurement, Ad Tech, and Data Science (MADS)

Amazon · Seattle, WA

Manager Master's

2026-05-30

WA 2026-05-30

Requirements

Bachelor's degree in Finance, Accounting, Business, Economics or a highly analytical field (e.g., Engineering, Math, and Computer Science)
5+ years of finance or a related analytical field experience
Experience coordinating between technical teams, peers and business stakeholders
5+ years of experience creating financial models and strategic analyses that support business decisions

Preferred

Experience in TM1, Data Warehouse and SQL
Experience with AI/ML technologies
Experience leading financial technology automation and process improvement initiatives with tech and non-tech teams
Advertising or Media experience is a plus

Responsibilities

Business Partnering & Performance Management
Serve as the finance partner for Performance Measurement and Infrastructure leadership
Advise engineering and product leaders on risks, opportunities, and trade-offs impacting quarterly and annual goals
Run weekly business reviews, define and report KPIs, and communicate financials to senior MADS leadership
Support monthly business reviews with insights, variance analysis, and recommendations
Strategic Analysis & Cost Management
Manage hardware cost analysis for Infrastructure, partnering with engineering on capacity planning and cost efficiency
Provide financial modeling and strategic analysis for PRFAQs, product roadmap decisions, and investment trade-offs
Deliver analyses that translate complex technical problems into actionable insights for senior leadership
Partner with BIE and analytics teams to build scalable dashboards and automated reporting
Cross-Functional Collaboration & Operational Excellence
Partner with product, engineering, data science, and sales teams to align strategy with business priorities
Collaborate across Advertising Finance to ensure consistency in planning and reporting
Leverage AI tools daily to raise the speed and quality of finance work, and build AI-powered solutions for the team
Drive process improvements that simplify and scale finance mechanisms, insisting on the highest standards in data accuracy and rigo

View full posting on CareerOneStop → ID: e9237370ca84

Machine Learning Research Scientist - Health AIML

Apple · Seattle, WA

Mid-level Doctorate

2026-05-30

WA 2026-05-30

Requirements

PhD in Computer Science/Engineering, Machine Learning, Statistics, Mathematics or related field.
Industry work experience.
Experience landing contributions to major LLM training runs.
Proven track record of publishing SOTA.
Strong skills with deep learning frameworks such as PyTorch, JAX, or TensorFlow.

Preferred

Experience in training and evaluating multimodal models.
Understand of time-series modeling, self-supervised learning, and cross-modal training.
Ability to thoroughly evaluate and improve deep learning architectures in a self-directed fashion.
Motivated by safely deploying LLMs in the health and fitness space.

Responsibilities

The Health AIML team is at the forefront of machine learning and health science at Apple. We are a close-knit team of research scientists, software engineers and machine learning engineers passionate about delivering innovative technologies that impact millions of users. We are looking for a Machine Learning Research Scientist with strong dedication to solving real-world problems in health and fitness that enrich our customers' lives.
We're developing next-generation multimodal models to create intelligent health and fitness experiences. This role requires someone with strong expertise in large multimodal models to work at the intersection of AI and health to build foundational models that scale to billions of users worldwide. Your work will shape the future of health and fitness technologies at Apple. We are looking for a senior researcher to guide multimodality research. You will focus on the development of foundational technology that enables models to understand health and fitness data.

View full posting on CareerOneStop → ID: 49ac6db33d5f

Principal Machine Learning Engineer, Content ML, Level 7

Snap Inc. · Seattle, WA

Senior Doctorate

2026-05-30

WA 2026-05-30

Requirements

9+ years of post-Bachelor's machine learning experience; or a Master's degree in a technical field + 8+ years of post-grad ML experience; or a PhD in a related technical field + 5+ years of post-grad ML experience
2+ years of experience with technical leadership or acting as the domain-expert to a technical organization
Experience developing and shipping performant and scalable machine learning models for recommendation or ranking use cases

Preferred

Advanced degree in a related field such as machine learning, computer vision, or mathematics
Experience with large-scale recommendation/ranking systems, multimodal modeling, or retrieval architectures
Experience with TensorFlow, PyTorch, or related deep learning frameworks
Background in integrating recommendation models into production pipelines
Experience partnering with cross-functional executives and management across a globally distributed organization and exercising sound judgment
Experience contributing to AI publications

Responsibilities

Lead the vision and roadmap for Snap's large-scale recommendation systems, elevating content discovery and personalization across Spotlight, Discover, and Friend Stories.
Technically lead a group of talented engineers from Content ML and Platform teams to operate and scale the existing recommender system.
Work with cross-team ML, Infra, and Research partners to design the next-gen recommender system and incorporate SOTA industry research in recommendation systems, foundation models, multimodal signal understanding, deep user understanding, and related areas. We actively participate in and publish at top-tier conferences.
Partner with engineers, product managers, research scientists, data science, and leadership to align on ML strategy and ensure technical investments support long-term company priorities.
Advance the ML tech stack for recommendations, improving scalability, efficiency, reliability, and overall system performance.
Stay up to date on emerging trends and advancements in the RecSys landscape and proactively identify opportunities to leverage these developments to further enhance Snap's content capabilities.
Advocate for and implement best practices in availability, scalability, experimentation rigor, operational excellence, and cost management.
*Knowledge, Skills & Abilities
Deep understanding of RecSys architectures and experience applying them to real-world production systems.
Strong foundation in machine learning, deep learning, and large-scale recommendation/ranking systems.
Experience leading teams or roadmaps focused on recommendations and/or personalization.
Ability to design, train, deploy, and optimize state-of-the-art machine learning models for performance, reliability, and scale.
Excellent programming and software engineering skills, with an emphasis on clean design and production-readiness.
Ability to quickly learn new technologies and apply them effectively in ambiguous problem spaces.
Skilled at solving complex technical challenges, influencing architecture decisions, and driving execution across multi-stakeholder environments.
Strong collaboration, communication, and mentorship abilities.

View full posting on CareerOneStop → ID: fbdb2787224b

Principal Machine Learning Engineer, Content ML, Level 7

Snap Inc. · Bellevue, WA

Senior Doctorate

2026-05-30

WA 2026-05-30

Requirements

9+ years of post-Bachelor's machine learning experience; or a Master's degree in a technical field + 8+ years of post-grad ML experience; or a PhD in a related technical field + 5+ years of post-grad ML experience
2+ years of experience with technical leadership or acting as the domain-expert to a technical organization
Experience developing and shipping performant and scalable machine learning models for recommendation or ranking use cases

Preferred

Advanced degree in a related field such as machine learning, computer vision, or mathematics
Experience with large-scale recommendation/ranking systems, multimodal modeling, or retrieval architectures
Experience with TensorFlow, PyTorch, or related deep learning frameworks
Background in integrating recommendation models into production pipelines
Experience partnering with cross-functional executives and management across a globally distributed organization and exercising sound judgment
Experience contributing to AI publications

Responsibilities

Lead the vision and roadmap for Snap's large-scale recommendation systems, elevating content discovery and personalization across Spotlight, Discover, and Friend Stories.
Technically lead a group of talented engineers from Content ML and Platform teams to operate and scale the existing recommender system.
Work with cross-team ML, Infra, and Research partners to design the next-gen recommender system and incorporate SOTA industry research in recommendation systems, foundation models, multimodal signal understanding, deep user understanding, and related areas. We actively participate in and publish at top-tier conferences.
Partner with engineers, product managers, research scientists, data science, and leadership to align on ML strategy and ensure technical investments support long-term company priorities.
Advance the ML tech stack for recommendations, improving scalability, efficiency, reliability, and overall system performance.
Stay up to date on emerging trends and advancements in the RecSys landscape and proactively identify opportunities to leverage these developments to further enhance Snap's content capabilities.
Advocate for and implement best practices in availability, scalability, experimentation rigor, operational excellence, and cost management.
*Knowledge, Skills & Abilities
Deep understanding of RecSys architectures and experience applying them to real-world production systems.
Strong foundation in machine learning, deep learning, and large-scale recommendation/ranking systems.
Experience leading teams or roadmaps focused on recommendations and/or personalization.
Ability to design, train, deploy, and optimize state-of-the-art machine learning models for performance, reliability, and scale.
Excellent programming and software engineering skills, with an emphasis on clean design and production-readiness.
Ability to quickly learn new technologies and apply them effectively in ambiguous problem spaces.
Skilled at solving complex technical challenges, influencing architecture decisions, and driving execution across multi-stakeholder environments.
Strong collaboration, communication, and mentorship abilities.

View full posting on CareerOneStop → ID: 328b35fd5ed8

Staff Data Scientist, Product

Google · Seattle, WA

Senior Master's

2026-05-30

WA 2026-05-30

Requirements

Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
10 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 8 years work experience plus a Master's degree).

Preferred

Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
12 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).

Responsibilities

Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.
Google is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. At Google, engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.
The US base salary range for this full-time position is $192,000-$278,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Provide analytical thought leadership through proactive and strategic contributions (e.g., suggests new analyses, infrastructure or experiments to drive improvements in the business).
Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, and implementation of analytical/statistical models, and presentation to stakeholders.
Develop solutions, lead, and manage problems that may be ambiguous and lacking clear precedent by framing problems, generating hypotheses, and making recommendations from a perspective that combines both, analytical and product-specific expertise.
Oversee the integration of cross-functional and cross-organizational project/process timelines, develop process improvements and recommendations, and help define operational goals and objectives.
Directly or indirectly oversee the contributions of others and develop colleagues' capabilities in the area of specialization.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 6269f214431d

Data Scientist

Deloitte · Boise, ID

Mid-level Doctorate

2026-05-30

ID 2026-05-30

Requirements

Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
5+ Years of Experience in a Data Science or Machine Learning role.
5+ Years of Experience Proficiency in programming languages such as Python or R.
5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
5+ Years of Experience with data manipulation and analysis libraries like pandas and NumPy
Limited immigration sponsorship may be available
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Master's or Ph.D. in a relevant field.
Experience with big data technologies like Spark or Hadoop.
Experience with deep learning frameworks like TensorFlow or PyTorch.
Familiarity with cloud platforms such as AWS, Azure, or GCP.
Experience with data visualization tools like Tableau or Power BI.
Analytical/ Decision Making Responsibilities
Analytical ability to manage multiple projects and prioritize tasks into manageable work products
Can operate independently or with minimum supervision
Excellent Written and Communication Skills
Ability to deliver technical demonstrations
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400-207,800
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Responsibilities

Work with stakeholders to identify business problems and formulate them as data science challenges.
Collect, clean, and explore large datasets to uncover trends and patterns.
Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
Validate and deploy models into production environments.
Communicate findings and insights to technical and non-technical audiences through data visualization and presentations.
Stay up to date with the latest trends and technologies in data science and machine learning.
Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeano
Ability to meet deadlines
Ability to provide clear guidance to others
Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.

View full posting on CareerOneStop → ID: 9f4391ee3526

Technical Project Manager - Machine Learning & Data Science

Cadmus · Boise, ID

Manager Bachelor's

2026-05-30

ID 2026-05-30

Requirements

5+ years of experience as a Technical Project Manager or Scrum Master, managing cross-functional projects.
Bachelor's degree in Information Systems, BI or Analytics or Engineering.
Strong technical proficiency and experience working with Machine Learning (ML) or Data Science/Artificial Intelligence (DS/AI) teams.
Experience managing large, ambiguous, cross-functional programs operating in fast-paced, highly collaborative environments.
Experience performing TPM best practices (e.g., schedule development and tracking, risk management, status reporting).
Experience regularly maintaining and reporting program data, preferably in Jira.
Deep understanding of Agile and SDLC methodologies and leading/modeling process adherence.
Excellent communication and problem-solving skills.
Ability to facilitate teams and individuals working collaboratively and efficiently.
A composed presence, business acumen, and ability to communicate at multiple levels of the organization.
Experience with automation and/or AI tools such as ChatGPT, Gemini, etc.
Preferred certifications: PMP or Scrum Master.
*Additional Information:
Candidates must be eligible to work in the United States as a U.S Perm Resident or U.S. Citizen.

Responsibilities

Manage and coordinate across multiple engineering teams delivering Machine Learning (ML) and Data Science/Artificial Intelligence (DS/AI) features and capabilities to support the broader vision, goals, and objectives of the company. Coordinate activities with internal teams and external partners.
Oversee end-to-end activities to ensure coordination and on-time delivery. Build integrated schedules based on an understanding team's activities and interdependencies between teams. Manage removing blockers, risks, and issues. Report program status.
Lead Agile ceremonies and assist with story definition, backlog prioritization, and dependency resolution.
Help Engineering teams balance scope, timeline, and quality to achieve optimal outcomes based on an understanding of priorities.
Advocate for clear priorities, technical excellence, process and best practices adherence, and customer-focused outcomes.
Influence without authority and drive consensus across diverse stakeholders.

View full posting on CareerOneStop → ID: 6009b75ef456

Technical Project Manager - Machine Learning & Data Science

Cadmus · Salem, OR

Manager Bachelor's

2026-05-30

OR 2026-05-30

Requirements

5+ years of experience as a Technical Project Manager or Scrum Master, managing cross-functional projects.
Bachelor's degree in Information Systems, BI or Analytics or Engineering.
Strong technical proficiency and experience working with Machine Learning (ML) or Data Science/Artificial Intelligence (DS/AI) teams.
Experience managing large, ambiguous, cross-functional programs operating in fast-paced, highly collaborative environments.
Experience performing TPM best practices (e.g., schedule development and tracking, risk management, status reporting).
Experience regularly maintaining and reporting program data, preferably in Jira.
Deep understanding of Agile and SDLC methodologies and leading/modeling process adherence.
Excellent communication and problem-solving skills.
Ability to facilitate teams and individuals working collaboratively and efficiently.
A composed presence, business acumen, and ability to communicate at multiple levels of the organization.
Experience with automation and/or AI tools such as ChatGPT, Gemini, etc.
Preferred certifications: PMP or Scrum Master.
*Additional Information:
Candidates must be eligible to work in the United States as a U.S Perm Resident or U.S. Citizen.

Responsibilities

Manage and coordinate across multiple engineering teams delivering Machine Learning (ML) and Data Science/Artificial Intelligence (DS/AI) features and capabilities to support the broader vision, goals, and objectives of the company. Coordinate activities with internal teams and external partners.
Oversee end-to-end activities to ensure coordination and on-time delivery. Build integrated schedules based on an understanding team's activities and interdependencies between teams. Manage removing blockers, risks, and issues. Report program status.
Lead Agile ceremonies and assist with story definition, backlog prioritization, and dependency resolution.
Help Engineering teams balance scope, timeline, and quality to achieve optimal outcomes based on an understanding of priorities.
Advocate for clear priorities, technical excellence, process and best practices adherence, and customer-focused outcomes.
Influence without authority and drive consensus across diverse stakeholders.

View full posting on CareerOneStop → ID: a610d659809f

Technical Project Manager - Machine Learning & Data Science

Cadmus · Helena, MT

Manager Bachelor's

2026-05-30

MT 2026-05-30

Requirements

5+ years of experience as a Technical Project Manager or Scrum Master, managing cross-functional projects.
Bachelor's degree in Information Systems, BI or Analytics or Engineering.
Strong technical proficiency and experience working with Machine Learning (ML) or Data Science/Artificial Intelligence (DS/AI) teams.
Experience managing large, ambiguous, cross-functional programs operating in fast-paced, highly collaborative environments.
Experience performing TPM best practices (e.g., schedule development and tracking, risk management, status reporting).
Experience regularly maintaining and reporting program data, preferably in Jira.
Deep understanding of Agile and SDLC methodologies and leading/modeling process adherence.
Excellent communication and problem-solving skills.
Ability to facilitate teams and individuals working collaboratively and efficiently.
A composed presence, business acumen, and ability to communicate at multiple levels of the organization.
Experience with automation and/or AI tools such as ChatGPT, Gemini, etc.
Preferred certifications: PMP or Scrum Master.
*Additional Information:
Candidates must be eligible to work in the United States as a U.S Perm Resident or U.S. Citizen.

Responsibilities

Manage and coordinate across multiple engineering teams delivering Machine Learning (ML) and Data Science/Artificial Intelligence (DS/AI) features and capabilities to support the broader vision, goals, and objectives of the company. Coordinate activities with internal teams and external partners.
Oversee end-to-end activities to ensure coordination and on-time delivery. Build integrated schedules based on an understanding team's activities and interdependencies between teams. Manage removing blockers, risks, and issues. Report program status.
Lead Agile ceremonies and assist with story definition, backlog prioritization, and dependency resolution.
Help Engineering teams balance scope, timeline, and quality to achieve optimal outcomes based on an understanding of priorities.
Advocate for clear priorities, technical excellence, process and best practices adherence, and customer-focused outcomes.
Influence without authority and drive consensus across diverse stakeholders.

View full posting on CareerOneStop → ID: e8819b62977f

Data Scientist - 3035128

Apex Systems, Inc. · Redmond, WA

Mid-level

2026-05-30

WA 2026-05-30

Requirements

5 years of experience in data analytics.
5 years of experience with SQL, bonus if familiar with SparkSQL, Databricks, or Azure Data Explorer.
2 years of experience with dashboarding tools, PowerBI preferred.
Proficient in Python, bonus if familiar with PySpark.
Able to work in a collaborative, diverse and fast-paced team.
Excellent analytical, and problem-solving skills and autonomy when faced with solving data problems.
Excellent verbal, visual and written communication skills.
Interest in games, bonus if experience in gaming industry.
Local to Seattle area.

Responsibilities

We are seeking a Data Scientist who is passionate about delivering high-impact, high-quality results to join the Player Data and Insights team. In this role, you will drive insights that inform the Game Studio strategy, with a focus on Consumer Products, Out of Game Experiences and Partnerships. You'll collaborate closely with the stakeholder teams to enhance consumer products reporting, analyze out of game experiences, evaluate opportunities, and recommend data-drive strategies to level up the connection between all parts of the franchise. This role is additional coverage for a team member on maternity leave, and you will be taking over additional duties beyond this specific scope as needed. These include maintaining forecasting models, assisting in franchise reporting and estimation, and collaborating with other data science vendors in the Beyond the Game space. Specific responsibilities include making recommendations to optimize business performance and evaluating the impact of various programs and initiatives on critical metrics, including tying out of game activities to in-game metrics. The ideal candidate will have experience with statistical analysis, data visualization tools, and strong communication skills to translate insights into actionable recommendations for both technical and non-technical stakeholders.
Partner with Consumer Products team and PADI data engineering to turn our Consumer Products data into clear reporting and actionable insights.
Identify key learnings from your analysis and synthesize them into recommendations for stakeholders.
Work collaboratively with other PADI data scientists to incorporate Beyond the Game findings into relevant major analyses and franchise beats.
Conduct data analysis as requested for stakeholder groups across Partnerships, Marketing and Consumer Products, including understanding ROI of out-of-game initiatives and optimizing for in-game metrics.
Be self-driven and show ability to deliver on ambiguous projects with incomplete or dirty data.
Maintain dashboards in PowerBI that enable stakeholders to understand the business and supporting onboarding to other self-service tools
Manipulate and analyze complex, high-volume, high-dimensionality data from varying sources using a variety of tools and data analysis techniques.

View full posting on CareerOneStop → ID: 0e84a5b54ed6

Staff Machine Learning Engineer, AI Research

Cribl, Inc · Helena, MT

Senior Doctorate

2026-05-30

MT 2026-05-30

B2B SAAS data observability software.Join the company that's building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world's biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructure r

View full posting on CareerOneStop → ID: f00681a785e1

Senior AI/ML Engineer

Eliassen Group · Boise, ID

Senior Bachelor's

2026-05-29

ID 2026-05-29

Requirements

10+ years in Software or IT with 7+ years in data analysis, AI engineering, and machine learning engineering.
Hands-on experience with LLM orchestration, integration, and vLLM-based inference for document understanding.
Experience with multi-agent AI systems, RAG pipelines, vector databases, and prompt engineering.
Strong Python skills with TensorFlow and PyTorch.
Proven AWS expertise including Bedrock, Lambda, ECS, SQS, SNS; additional experience with S3, ELB/ALB, Aurora RDS preferred.
Experience with image transformer models for document image understanding, including Microsoft DiT.
Experience with self-supervised learning and leveraging pre-trained transformer backbones for document AI tasks.
Integration of transformers into OCR pipelines and collaboration with OCR technologies.
OpenCV-based image processing for document analysis.
CI/CD with Terraform, GitLab, and GitLab Runner.
Nice to have: Java, Spring Boot, Spring/JPA, Hibernate/MyBatis, JBoss/Fuse Camel/AMQ, SQL, Oracle, REST services.
Familiarity with AI coding tools such as Claude and Codex.
Strong problem solving and communication skills with ability to work independently.
AWS certification required such as Solutions Architect Associate, Developer Associate, Machine Learning Engineer Associate, SysOps Admin Associate, or Cloud Practitioner.
Public Trust eligibility and awareness of 3 to 6 week clearance timeline, including fingerprinting. Must have been a U.S. permanent resident for at least the last 2 years.

Education

BA/BS in Computer Science, Machine Learning, or related field with 10 years of experience, or MA/MS or higher with 8 years of experience.
Additional experience does not substitute for the education requirement.
*_Recruitment Transparency Notice_
*_Eliassen Group values transparency in our recruitment practices. Please be advised that Eliassen Group utilizes artificial intelligence (AI) tools as part of its initial application screening_ _and hiring_ _process. You may receive email and SMS notifications from the Eliassen Virtual Recruiting Team (_ _noreply@eliassen.com_ _, 781-808-2924) inviting you to complete a brief voice screening as part of your application process. These tools assist our hiring teams in different ways, including but not limited to, assistance in reviewing application materials to help identify candidates whose qualifications most closely match the requirements of the position. All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring decisions are made. The use of AI in our process is intended to support fairness, efficiency, and consistency, and Eliassen Group takes measures to prevent bias or discrimination in connection with its hiring practices. By proceeding, you acknowledge, agree, and consent to Eliassen Group's use of these tools, including AI tools, as part of the application and hiring process._
_Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range._

Responsibilities

Engineer AI solutions using LLM providers and implement complex multi-agent workflows.
Design and develop predictive models using regression, classification, clustering, and neural networks.
Build RAG pipelines, integrate vector databases, and apply prompt engineering with LangChain or LangGraph.
Develop end-to-end AI/ML/NLP plans compliant with cybersecurity policies.
Apply software engineering best practices for maintainable, efficient, reliable, and secure code.
Identify and resolve performance bottlenecks and security vulnerabilities.
Implement CI/CD using Terraform, GitLab, and GitLab Runner with automated testing and security scans.
Support production deployments, smoke testing, monitoring, root cause analysis, and issue resolution.
Collaborate in Agile ceremonies, estimate work, and participate in reviews, demos, and retrospectives.

View full posting on CareerOneStop → ID: fcb795557c82

Data Scientist I, PXT Central Science

Amazon · Bellevue, WA

Entry-level Doctorate

2026-05-29

WA 2026-05-29

Requirements

1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
Experience working with or evaluating AI systems
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

Own the design, development, and maintenance of scalable models and prototypes leveraging statistical, machine learning, or GenAI methodologies to enhance employee experience.
Partner with scientists, engineers, and product leaders to solve for employee experience defects using scientific approaches, building new services and tools that deliverable measurable impact.
Author and maintain detailed technical documentation related to the projects you drive.
Communicate results to diverse audiences of varying technical background with effective writing, visualizations, and presentations
Stay current with emerging methods and technologies, and implement them strategically to amplify the team's impact.

View full posting on CareerOneStop → ID: 4295c5f82a8c

Data Scientist I, PXT Central Science

Amazon · Seattle, WA

Entry-level Doctorate

2026-05-29

WA 2026-05-29

Requirements

1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
Experience working with or evaluating AI systems
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

Own the design, development, and maintenance of scalable models and prototypes leveraging statistical, machine learning, or GenAI methodologies to enhance employee experience.
Partner with scientists, engineers, and product leaders to solve for employee experience defects using scientific approaches, building new services and tools that deliverable measurable impact.
Author and maintain detailed technical documentation related to the projects you drive.
Communicate results to diverse audiences of varying technical background with effective writing, visualizations, and presentations
Stay current with emerging methods and technologies, and implement them strategically to amplify the team's impact.

View full posting on CareerOneStop → ID: 96c7b1b6f413

Data Scientist, Demand Forecasting

Amazon · Bellevue, WA

Mid-level Bachelor's

2026-05-29

WA 2026-05-29

Requirements

1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
Bachelor's degree

Preferred

Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)

Responsibilities

Design and run rigorous experiments at scale to evaluate and improve foundation model performance across hundreds of millions of products, geographies, and business verticals
Lead the end-to-end lifecycle of forecasting models - from research and experimentation through production launch - including defining success metrics, obtaining stakeholder sign-off, and managing rollout
Conduct online and offline labs to measure the real-world impact of forecast improvements beyond accuracy, including downstream supply chain, inventory, and financial outcomes
Develop and deploy production-grade deep learning and statistical models using Python, Scala, SQL, and related tools
Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform model development
Translate complex research findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
Contribute to Amazon's scientific community and the broader research field through collaboration and publication in top-tier venues
No two days look the same, but most will involve some combination of deep technical work, cross-functional collaboration, and scientific thinking at a scale you won't find anywhere else.
You might start the morning reviewing the results of an experiment running across hundreds of millions of products - analyzing whether a new foundation model variant is improving generalization on cold-start items, or whether a novel data generation approach is meaningfully shifting forecast quality. You'll dig into the numbers, form a hypothesis, and design the next iteration.
Later in the day, you could be in a stakeholder review, walking business and engineering partners through a set of launch metrics - explaining not just forecast accuracy, but the downstream supply chain and financial impact your model is driving. Getting a model to production at Amazon requires rigor: you'll define success criteria, run online and offline labs to validate real-world impact, and build the case for sign-off across technical and business stakeholders.
You'll write code - Python, Scala, SQL - to process and analyze data at a scale most scientists never encounter. You'll collaborate closely with scientists, engineers, and business teams, and contribute to research that has a real chance of being published and advancing the field.
The work is hard, the problems are unsolved, and the impact is immediate. If you want to do research that ships - this is where you do it.
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
Medical, Dental, and Vision Coverage
Maternity and Parental Leave Options
Paid Time Off (PTO)
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!

View full posting on CareerOneStop → ID: db6094b0d370

Machine Learning Engineer, Level 4

Snap Inc. · Seattle, WA

Mid-level Doctorate

2026-05-29

WA 2026-05-29

Requirements

Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
3+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field
Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning

Preferred

Advanced degree in computer science or related field
Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks
Experience working with machine learning, ranking infrastructures, and system design

Responsibilities

Build and deploy machine learning models that power core products, serving millions of Snapchatters
Apply modern ML techniques to solve large-scale, real-world problems
Own the full ML lifecycle from data analysis to production deployment
Partner with cross-functional teams to prototype and launch ML-driven features
Utilize AI tools to design and ship scalable services while upholding rigorous standards for code correctness, security, and production
Knowledge, Skills & Abilities:
Strong understanding of machine learning approaches and algorithms
Able to prioritize duties and work well on your own
Ability to work with both internal and external partners
Skilled at solving open ambiguous problems
Strong collaboration and mentorship skills
Proficiency in, or a strong aptitude for, leveraging AI tools to streamline development, paired with the critical judgment to audit generated output for architectural integrity, performance bottlenecks, and security risks
Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices

View full posting on CareerOneStop → ID: 3c9d2da8f510

Machine Learning Engineer, Level 4

Snap Inc. · Bellevue, WA

Mid-level Doctorate

2026-05-29

WA 2026-05-29

Requirements

Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
3+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field
Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning

Preferred

Advanced degree in computer science or related field
Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks
Experience working with machine learning, ranking infrastructures, and system design

Responsibilities

Build and deploy machine learning models that power core products, serving millions of Snapchatters
Apply modern ML techniques to solve large-scale, real-world problems
Own the full ML lifecycle from data analysis to production deployment
Partner with cross-functional teams to prototype and launch ML-driven features
Utilize AI tools to design and ship scalable services while upholding rigorous standards for code correctness, security, and production
Knowledge, Skills & Abilities:
Strong understanding of machine learning approaches and algorithms
Able to prioritize duties and work well on your own
Ability to work with both internal and external partners
Skilled at solving open ambiguous problems
Strong collaboration and mentorship skills
Proficiency in, or a strong aptitude for, leveraging AI tools to streamline development, paired with the critical judgment to audit generated output for architectural integrity, performance bottlenecks, and security risks
Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices

View full posting on CareerOneStop → ID: 357ea433c4b5

Manager - Data Science / Data Lake

Deloitte · Seattle, WA

Manager Bachelor's

2026-05-29

WA 2026-05-29

Requirements

10+ years of experience in analytics consulting, cybersecurity analytics, security operations, or a combination of these
10+ years of experience with artificial intelligence development tools or frameworks such as vector databases, LangChain, or CrewAI
10+ years of experience using Python, Structured Query Language (SQL), R, or SAS to prepare data for analysis, engineer features, visualize data, or support machine learning workflows
Experience working with cyber security cloud platforms such as Google SecOps, Amazon Web Services (AWS), or Microsoft Azure, and exposure to security operations center (SOC) threat hunting or incident response
Bachelor's degree in Engineering, Mathematics, Statistics, Computer Science, Cybersecurity, or a field aligned to the role; or 4 years of equivalent professional experience
Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
Limited immigration sponsorship may be available.

Preferred

Experience supporting the design, development, or deployment of enterprise data science or artificial intelligence solutions
Experience applying artificial intelligence, machine learning, or advanced data engineering to cybersecurity use cases such as detection engineering or threat response acceleration
Experience parsing and normalizing cyber or information technology telemetry datasets
Experience with PyTorch, Keras, TensorFlow, Scikit-learn, NumPy, or SciPy
Experience with Apache Kafka, Storm, or Spark
Experience creating client-ready materials using Microsoft PowerPoint or Microsoft Visio
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: 6e0e84031d18

Principal Machine Learning Engineer

Cisco · Bellevue, WA

Senior Doctorate

2026-05-29

WA 2026-05-29

Requirements

PhD in Computer Science, or related quantitative field, plus7+ years of industry research experience.
Proven track record in at least one of the following areas: large language modeling for both structure and unstructured data, deep learning-based time series modeling, advanced anomaly detection, and multi-modality modeling.
Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow)
Experience translating research ideas into production systems.

Preferred

Deep NLP & Domain-Adapted LLMs: Background in building and adapting large-scale language models (e.g., T5, BERT, LLaMA, GPTs) for specialized domains including structured/unstructured logs, text, and event sequences.
Log Analytics Expertise - In-depth knowledge of structured/unstructured system logs, event sequence analysis, anomaly detection, and root cause identification.
Advanced Anomaly Detection - Experience creating robust, scalable approaches (statistical, deep learning, or hybrid) for high-volume, real-time logs data.
Multi-Modal AI Modeling - Strong track record fusing logs, time series, traces, tabular data, and graphs for foundation models tackling complex operational insights.
Large-Scale Training & Optimization - Experience optimizing model architectures, distributed training pipelines, and inference efficiency to minimize cost and latency while preserving accuracy.
MLOps & Continuous Learning - Fluency in automated retraining, drift detection, incremental updates, and production monitoring of ML models.
Strong Research Track Record - Publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ACL, KDD) demonstrating contributions to state-of-the-art methods and real-world applications.
At Cisco, we're revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond. We've been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you'll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.
We are Cisco, and our power starts with you.
*Message to applicants applying to work in the U.S. and/or Canada:

View full posting on CareerOneStop → ID: 3a0d2e8cd412

Principal Machine Learning Engineer

Cisco · Seattle, WA

Senior Doctorate

2026-05-29

WA 2026-05-29

Requirements

PhD in Computer Science, or related quantitative field, plus7+ years of industry research experience.
Proven track record in at least one of the following areas: large language modeling for both structure and unstructured data, deep learning-based time series modeling, advanced anomaly detection, and multi-modality modeling.
Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow)
Experience translating research ideas into production systems.

Preferred

Deep NLP & Domain-Adapted LLMs: Background in building and adapting large-scale language models (e.g., T5, BERT, LLaMA, GPTs) for specialized domains including structured/unstructured logs, text, and event sequences.
Log Analytics Expertise - In-depth knowledge of structured/unstructured system logs, event sequence analysis, anomaly detection, and root cause identification.
Advanced Anomaly Detection - Experience creating robust, scalable approaches (statistical, deep learning, or hybrid) for high-volume, real-time logs data.
Multi-Modal AI Modeling - Strong track record fusing logs, time series, traces, tabular data, and graphs for foundation models tackling complex operational insights.
Large-Scale Training & Optimization - Experience optimizing model architectures, distributed training pipelines, and inference efficiency to minimize cost and latency while preserving accuracy.
MLOps & Continuous Learning - Fluency in automated retraining, drift detection, incremental updates, and production monitoring of ML models.
Strong Research Track Record - Publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ACL, KDD) demonstrating contributions to state-of-the-art methods and real-world applications.
At Cisco, we're revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond. We've been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you'll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.
We are Cisco, and our power starts with you.
*Message to applicants applying to work in the U.S. and/or Canada:

View full posting on CareerOneStop → ID: 05d91fa78067

Sr. Machine Learning - Compiler Engineer III, AWS Neuron, Annapurna Labs

Amazon · Seattle, WA

Senior Doctorate

2026-05-29

WA 2026-05-29

Requirements

Bachelor's degree in computer science or equivalent
5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
3+ years of experience in developing compiler features and optimizations
Proficiency with 1 or more of the following programming languages: C++ (preferred), Python

Preferred

Master or PhD degree in computer science or equivalent
Proficiency with compiler design, resource management, instruction scheduling, memory allocation, data transfer optimization, compute graph optimization, code generation, and Instruction Set Architecture
Experience with LLVM and/or MLIR
Experience in LLM, Vision or other deep-learning models

Responsibilities

You will design, implement, test, deploy and maintain innovative software solutions to transform Neuron compiler's performance, stability and user-interface. You will work side by side with chip architects, runtime/OS engineers, scientists and ML Apps teams to seamlessly deploy cutting edge ML models from our customers on AWS accelerators with optimal cost/performance benefits. You will have opportunity to become front-face of Neuron Compiler to work with open-source communities (e.g., StableHLO, OpenXLA, MLIR) and influence industry wide partners to pioneer optimizing cutting-edge ML workloads on AWS software and hardware. You will also work on building innovative features that will deliver best possible experiences for our customers - developers across the globe.
As you design and code solutions to help our team drive efficiencies in compiler architecture, you'll create compiler optimization and verification passes, build features surface features and peculiarities of AWS accelerators to developers, implement tools to analyze numerical errors, and resolve the root cause of compiler defects. You'll also participate in design discussions, code review, and communicate with internal (other Neuron SDK and Amazon wide teams) and external stakeholders (open-source communities and respond to Neuron compiler related questions in open forums, e.g. GitHub). Lastly, work in a startup-like development environment, where you're always working on the most important stuff.

View full posting on CareerOneStop → ID: 44925d76575d

Senior AI/ML Engineer

Eliassen Group · Olympia, WA

Senior Bachelor's

2026-05-29

WA 2026-05-29

Requirements

10+ years in Software or IT with 7+ years in data analysis, AI engineering, and machine learning engineering.
Hands-on experience with LLM orchestration, integration, and vLLM-based inference for document understanding.
Experience with multi-agent AI systems, RAG pipelines, vector databases, and prompt engineering.
Strong Python skills with TensorFlow and PyTorch.
Proven AWS expertise including Bedrock, Lambda, ECS, SQS, SNS; additional experience with S3, ELB/ALB, Aurora RDS preferred.
Experience with image transformer models for document image understanding, including Microsoft DiT.
Experience with self-supervised learning and leveraging pre-trained transformer backbones for document AI tasks.
Integration of transformers into OCR pipelines and collaboration with OCR technologies.
OpenCV-based image processing for document analysis.
CI/CD with Terraform, GitLab, and GitLab Runner.
Nice to have: Java, Spring Boot, Spring/JPA, Hibernate/MyBatis, JBoss/Fuse Camel/AMQ, SQL, Oracle, REST services.
Familiarity with AI coding tools such as Claude and Codex.
Strong problem solving and communication skills with ability to work independently.
AWS certification required such as Solutions Architect Associate, Developer Associate, Machine Learning Engineer Associate, SysOps Admin Associate, or Cloud Practitioner.
Public Trust eligibility and awareness of 3 to 6 week clearance timeline, including fingerprinting. Must have been a U.S. permanent resident for at least the last 2 years.

Education

BA/BS in Computer Science, Machine Learning, or related field with 10 years of experience, or MA/MS or higher with 8 years of experience.
Additional experience does not substitute for the education requirement.
*_Recruitment Transparency Notice_
*_Eliassen Group values transparency in our recruitment practices. Please be advised that Eliassen Group utilizes artificial intelligence (AI) tools as part of its initial application screening_ _and hiring_ _process. You may receive email and SMS notifications from the Eliassen Virtual Recruiting Team (_ _noreply@eliassen.com_ _, 781-808-2924) inviting you to complete a brief voice screening as part of your application process. These tools assist our hiring teams in different ways, including but not limited to, assistance in reviewing application materials to help identify candidates whose qualifications most closely match the requirements of the position. All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring decisions are made. The use of AI in our process is intended to support fairness, efficiency, and consistency, and Eliassen Group takes measures to prevent bias or discrimination in connection with its hiring practices. By proceeding, you acknowledge, agree, and consent to Eliassen Group's use of these tools, including AI tools, as part of the application and hiring process._
_Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range._

Responsibilities

Engineer AI solutions using LLM providers and implement complex multi-agent workflows.
Design and develop predictive models using regression, classification, clustering, and neural networks.
Build RAG pipelines, integrate vector databases, and apply prompt engineering with LangChain or LangGraph.
Develop end-to-end AI/ML/NLP plans compliant with cybersecurity policies.
Apply software engineering best practices for maintainable, efficient, reliable, and secure code.
Identify and resolve performance bottlenecks and security vulnerabilities.
Implement CI/CD using Terraform, GitLab, and GitLab Runner with automated testing and security scans.
Support production deployments, smoke testing, monitoring, root cause analysis, and issue resolution.
Collaborate in Agile ceremonies, estimate work, and participate in reviews, demos, and retrospectives.

View full posting on CareerOneStop → ID: 8f083dedf38a

Senior AI/ML Engineer

Eliassen Group · Salem, OR

Senior Bachelor's

2026-05-29

OR 2026-05-29

Requirements

10+ years in Software or IT with 7+ years in data analysis, AI engineering, and machine learning engineering.
Hands-on experience with LLM orchestration, integration, and vLLM-based inference for document understanding.
Experience with multi-agent AI systems, RAG pipelines, vector databases, and prompt engineering.
Strong Python skills with TensorFlow and PyTorch.
Proven AWS expertise including Bedrock, Lambda, ECS, SQS, SNS; additional experience with S3, ELB/ALB, Aurora RDS preferred.
Experience with image transformer models for document image understanding, including Microsoft DiT.
Experience with self-supervised learning and leveraging pre-trained transformer backbones for document AI tasks.
Integration of transformers into OCR pipelines and collaboration with OCR technologies.
OpenCV-based image processing for document analysis.
CI/CD with Terraform, GitLab, and GitLab Runner.
Nice to have: Java, Spring Boot, Spring/JPA, Hibernate/MyBatis, JBoss/Fuse Camel/AMQ, SQL, Oracle, REST services.
Familiarity with AI coding tools such as Claude and Codex.
Strong problem solving and communication skills with ability to work independently.
AWS certification required such as Solutions Architect Associate, Developer Associate, Machine Learning Engineer Associate, SysOps Admin Associate, or Cloud Practitioner.
Public Trust eligibility and awareness of 3 to 6 week clearance timeline, including fingerprinting. Must have been a U.S. permanent resident for at least the last 2 years.

Education

BA/BS in Computer Science, Machine Learning, or related field with 10 years of experience, or MA/MS or higher with 8 years of experience.
Additional experience does not substitute for the education requirement.
*_Recruitment Transparency Notice_
*_Eliassen Group values transparency in our recruitment practices. Please be advised that Eliassen Group utilizes artificial intelligence (AI) tools as part of its initial application screening_ _and hiring_ _process. You may receive email and SMS notifications from the Eliassen Virtual Recruiting Team (_ _noreply@eliassen.com_ _, 781-808-2924) inviting you to complete a brief voice screening as part of your application process. These tools assist our hiring teams in different ways, including but not limited to, assistance in reviewing application materials to help identify candidates whose qualifications most closely match the requirements of the position. All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring decisions are made. The use of AI in our process is intended to support fairness, efficiency, and consistency, and Eliassen Group takes measures to prevent bias or discrimination in connection with its hiring practices. By proceeding, you acknowledge, agree, and consent to Eliassen Group's use of these tools, including AI tools, as part of the application and hiring process._
_Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range._

Responsibilities

Engineer AI solutions using LLM providers and implement complex multi-agent workflows.
Design and develop predictive models using regression, classification, clustering, and neural networks.
Build RAG pipelines, integrate vector databases, and apply prompt engineering with LangChain or LangGraph.
Develop end-to-end AI/ML/NLP plans compliant with cybersecurity policies.
Apply software engineering best practices for maintainable, efficient, reliable, and secure code.
Identify and resolve performance bottlenecks and security vulnerabilities.
Implement CI/CD using Terraform, GitLab, and GitLab Runner with automated testing and security scans.
Support production deployments, smoke testing, monitoring, root cause analysis, and issue resolution.
Collaborate in Agile ceremonies, estimate work, and participate in reviews, demos, and retrospectives.

View full posting on CareerOneStop → ID: d5fd6d64d416

Senior AI/ML Engineer

Eliassen Group · Helena, MT

Senior Bachelor's

2026-05-29

MT 2026-05-29

Requirements

10+ years in Software or IT with 7+ years in data analysis, AI engineering, and machine learning engineering.
Hands-on experience with LLM orchestration, integration, and vLLM-based inference for document understanding.
Experience with multi-agent AI systems, RAG pipelines, vector databases, and prompt engineering.
Strong Python skills with TensorFlow and PyTorch.
Proven AWS expertise including Bedrock, Lambda, ECS, SQS, SNS; additional experience with S3, ELB/ALB, Aurora RDS preferred.
Experience with image transformer models for document image understanding, including Microsoft DiT.
Experience with self-supervised learning and leveraging pre-trained transformer backbones for document AI tasks.
Integration of transformers into OCR pipelines and collaboration with OCR technologies.
OpenCV-based image processing for document analysis.
CI/CD with Terraform, GitLab, and GitLab Runner.
Nice to have: Java, Spring Boot, Spring/JPA, Hibernate/MyBatis, JBoss/Fuse Camel/AMQ, SQL, Oracle, REST services.
Familiarity with AI coding tools such as Claude and Codex.
Strong problem solving and communication skills with ability to work independently.
AWS certification required such as Solutions Architect Associate, Developer Associate, Machine Learning Engineer Associate, SysOps Admin Associate, or Cloud Practitioner.
Public Trust eligibility and awareness of 3 to 6 week clearance timeline, including fingerprinting. Must have been a U.S. permanent resident for at least the last 2 years.

Education

BA/BS in Computer Science, Machine Learning, or related field with 10 years of experience, or MA/MS or higher with 8 years of experience.
Additional experience does not substitute for the education requirement.
*_Recruitment Transparency Notice_
*_Eliassen Group values transparency in our recruitment practices. Please be advised that Eliassen Group utilizes artificial intelligence (AI) tools as part of its initial application screening_ _and hiring_ _process. You may receive email and SMS notifications from the Eliassen Virtual Recruiting Team (_ _noreply@eliassen.com_ _, 781-808-2924) inviting you to complete a brief voice screening as part of your application process. These tools assist our hiring teams in different ways, including but not limited to, assistance in reviewing application materials to help identify candidates whose qualifications most closely match the requirements of the position. All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring decisions are made. The use of AI in our process is intended to support fairness, efficiency, and consistency, and Eliassen Group takes measures to prevent bias or discrimination in connection with its hiring practices. By proceeding, you acknowledge, agree, and consent to Eliassen Group's use of these tools, including AI tools, as part of the application and hiring process._
_Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range._

Responsibilities

Engineer AI solutions using LLM providers and implement complex multi-agent workflows.
Design and develop predictive models using regression, classification, clustering, and neural networks.
Build RAG pipelines, integrate vector databases, and apply prompt engineering with LangChain or LangGraph.
Develop end-to-end AI/ML/NLP plans compliant with cybersecurity policies.
Apply software engineering best practices for maintainable, efficient, reliable, and secure code.
Identify and resolve performance bottlenecks and security vulnerabilities.
Implement CI/CD using Terraform, GitLab, and GitLab Runner with automated testing and security scans.
Support production deployments, smoke testing, monitoring, root cause analysis, and issue resolution.
Collaborate in Agile ceremonies, estimate work, and participate in reviews, demos, and retrospectives.

View full posting on CareerOneStop → ID: 6ea19695b6ae

Principal Data Scientists

T-Mobile USA, Inc. · Bellevue, WA

Senior Master's

2026-05-29

WA 2026-05-29

T-Mobile USA, Inc. seeks Principal Data Scientists in Bellevue, WA to implement and maintain modeling pipelines in Python, ensuring statistical accuracy and version control in collaboration with data engineering teams (10%). Communicate complex findings clearly to technical and non-technical stakeho

View full posting on CareerOneStop → ID: 5d0ca1841abb

Principal Engineer, Search and AI Infrastructure, Machine Learning Platform & Infrastructure

Apple · Seattle, WA

Senior Doctorate

2026-05-29

WA 2026-05-29

Requirements

Bachelor's degree in Computer Science, relevant technical field, or equivalent practical experience
Strong background in computer science: algorithms, data structures and system design
15+ year experience on large scale distributed system design, operation and optimization with over 10 years of leading teams
Has managed work across a large organization, demonstrated the ability to develop strong leaders, with a consistent track record of executional excellence
Excellent collaboration skills, excelling at both high-level thinking & execution as well as in the ability to influence and inspire others to achieve a common goal

Preferred

Preferred qualifications
Master's degree or PhD in Computer Science or related technical fields
Experience supporting distributed training inference workloads in production, ML systems performance profiling, debugging, and optimization
Proficiency in cloud-native architectures and orchestration platforms (e.g., Kubernetes)
Familiar with fundamental Deep Learning architectures such as Transformers, Encoder/Decoder models
Familiarity with Nvidia TensorRT-LLM, vLLLM, DeepSpeed, Nvidia Triton Server etc
Hands-on experience working with ML accelerators such as GPUs and TPUs

Responsibilities

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
Do you want to make Apple products more intelligent for our users? As part of Apple Services Engineering organization, Machine Learning Platform & Infrastructure team is building groundbreaking technology for search, natural language processing, artificial intelligence and machine learning. Our infrastructure is the back-bone of Apple Intelligence. It powers the largest Apple foundation models on servers and a wide gamut of services at Apple including Siri, Apple Music, AppleTV, AppStore, Photos & Camera, Spotlight, Safari, and upcoming ever exciting Apple products serving millions of queries every day with incredible low latencies, drawing every ounce of compute from our hardware.
As part of this group, you will work with one of the most exciting high performance computing environments, with petabytes of data, millions of queries per second, and have an opportunity to imagine and build products that delight our customers every single day. You will have a chance to work on optimizing billions of parameter language and vision and speech models using state of the art technologies and make it run at scale of Apple.
We are seeking a Principal Engineer to provide leadership in building and evolving next-generation AI infrastructure for search and other product needs at Apple. In this role, you will shape the architecture and long-term technical strategy for large-scale inference systems that handle both internal workload and production traffic, integrate and evolve the web-scale search systems, work at the intersection of product innovation, AI research, and large scale distributed systems.
We design, build and maintain infrastructure to support features that empower billions of Apple users. We take full end-to-end ownership of our services, driving them through every stage meticulously, encompassing conception, design, implementation, deployment, and maintenance. As a result, each one of us takes our responsibilities seriously. In this team, you'll have the opportunity to work on incredibly complex large scale systems with trillions of records and petabytes of data, work along side teams to optimize inference for cutting edge model architectures, and build production grade solutions for millions of customers in real time.

View full posting on CareerOneStop → ID: 89bd7475abc2

Sr Machine Learning Engineer, AI Research

Cribl, Inc · Helena, MT

Senior Doctorate

2026-05-29

MT 2026-05-29

B2B SAAS data observability software.Join the company that's building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world's biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructure r

View full posting on CareerOneStop → ID: af0480568034

Business Data Scientist, Ads Marketing Analytics

Google · Kirkland, WA

Mid-level Doctorate

2026-05-28

WA 2026-05-28

Requirements

Master's degree in a quantitative field (Statistics, Mathematics, Data Science, Bioinformatics, Economics, etc.) or equivalent practical experience
3 years of experience in a data science field.
Experience with statistical software (e.g., R, Python, MATLAB) and database languages (i.e., SQL).
Experience using analytics to solve product or business problems, querying databases or statistical analysis.

Preferred

PhD in Statistics or related quantitative discipline.
2 years of experience, including statistical data analysis such as generalized linear models, multivariate analysis, clustering/segmentation and sampling methods.
Experience in controlled experiment design and causal inference methods.
Ability to prioritize requests and partner well in an environment with competing demands from stakeholders.
Ability to convince business stakeholders and communicate analysis insights to non-technical audiences and willingness to both teach others and learn new techniques.
Excellent communication and team-work including problem-solving skills.

Responsibilities

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.
Google Ads Marketing helps advertisers of all sizes succeed with digital marketing. In this role, you will work with a team to advance marketing science for customers using Google's advertising solutions. This unique opportunity applies Data Science tools to accelerate Ads business growth, working cross-functionally with Sales, Marketing, and Product teams.
As a Data Scientist on this team, you will perform deep data analytics, drive experimentation and measurement, and advance machine learning modeling to support global marketing programs.
Collaborating with a multidisciplinary team of marketers, product managers, data scientists, and engineers, you will leverage underlying data to align on key metrics and methodologies. Your insights will enable marketers to develop highly effective programs. Using core Data Science expertise, you will design, prototype, and build scalable analysis pipelines to support campaigns. You will perform analytics, execute experimentation, and conduct incrementality measurement to inform strategic decisions across the entire Ads Marketing lifecycle-from acquisition and onboarding to growth and retention.
You will build investigative frameworks and measurement capabilities to generate data-driven insights that drive business growth. You will effectively communicate your investigative results to marketing partners and leadership to inform critical decision-making.
The US base salary range for this full-time position is $138,000-$198,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Work with large, complex data sets. Solve analysis problems, applying advanced investigative methods (such as statistical and machine learning models) as needed. Conduct analysis that includes problem formulation, data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
Design and analyze controlled experiments or counterfactual causal inference studies to examine the incremental impact of Ads marketing programs.
Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed.
Interact cross-functionally, making business recommendations (e.g. cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
Develop and automate reports, iteratively build and prototype dashboards to provide insights at scale, solving for business priorities.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 8bedd46a44c4

Data Scientist II, Middle Mile Transportation Science team

Amazon · Bellevue, WA

Mid-level Master's

2026-05-28

WA 2026-05-28

Requirements

Master's degree in Science, Technology, Engineering, or Mathematics (STEM)
2+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
Proficiency in statistical modeling and machine learning - time-series forecasting, regression, tree-based methods, and deep learning.
Demonstrated ability to communicate technical results to non-technical business audiences.

Preferred

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience

Responsibilities

Design and implement complex ML and optimization solutions (forecasting, MIP/LP, simulation, Deep learning / foundation model);
Drive end-to-end delivery of scalable models - from data exploration and feature engineering through training, evaluation, deployment, and post-launch monitoring;
Develop new modeling patterns and analytical frameworks for forecasting (multivariate, hierarchical, causal-DAG, model-chaining) and optimization;
Build robust model validation, backtesting, and monitoring pipelines; identify and eliminate sources of leakage, bias, and silent failure;
Define and own model performance metrics (e.g., WAPE) tied to business outcomes;
Partner with Data Engineering and Software Development to productionize models and define I/O contracts, packaging, and model CI/CD;
Excellent communication to present findings, tradeoffs, and recommendations clearly to stakeholders and senior leadership.

View full posting on CareerOneStop → ID: d4f4fd89e4ba

AI/ML Engineer

Raft LLC · Tacoma, WA

Mid-level Doctorate

2026-05-28

WA 2026-05-28

Requirements

3+ years of relevant hands-on experience, or a PhD in a related field with demonstrated practical application
Practical experience in Machine Learning models and Software Engineering
A passion for (and track record of) innovation, an interest in exploring and leveraging new data modalities, and working across interdisciplinary teams
Experience building and maintaining machine learning platforms and pipelines
Experience in building machine learning models, and
Experience in using data processing frameworks (Apache Spark preferred)
Practical programming and scripting skills (Python preferred)
Fast learner, analytical thinker, creative, hands-on, strong communication skills
Able to work both independently and as part of a team
Excellent problem-solving skills and attention to detail.
Proven experience with modern software development and engineering practices including scrum/agile, Git, and DevOps
Obtain Security+ within the first 90 days of employment with Raft
Ability to obtaina Top Secret clearance with potential for SCI

Preferred

Publications or GitHub repos showcasing your skills

Education

Annual budget for your tech/gadgets needs
Generous Referral Bonuses
Annual budget for your tec

Responsibilities

*AI/ML Engineer,
you will collaborate with a cross-functional data team comprising of DevSecOps engineers, Product Owners, Data Engineers and Data Scientists. Your primary responsibility will be to develop machine learning models that are integral to a larger pipeline delivering value to our end customers.

View full posting on CareerOneStop → ID: 754c9024cb6a

Associate AI/ML Engineer

Raft LLC · Tacoma, WA

Entry-level Doctorate

2026-05-28

WA 2026-05-28

Requirements

1+ years of relevant hands-on experience, or a PhD in a related field with demonstrated practical application
Practical experience in Machine Learning models and Software Engineering
A passion for (and track record of) innovation, an interest in exploring and leveraging new data modalities, and working across interdisciplinary teams
Experience building and maintaining machine learning platforms and pipelines
Experience in building machine learning models, and
Experience in using data processing frameworks (Apache Spark preferred)
Practical programming and scripting skills (Python preferred)
Fast learner, analytical thinker, creative, hands-on, strong communication skills
Able to work both independently and as part of a team
Excellent problem-solving skills and attention to detail.
Proven experience with modern software development and engineering practices including scrum/agile, Git, and DevOps
Obtain Security+ within the first 90 days of employment with Raft
Ability to obtaina Top Secret clearance with potential for SCI

Preferred

Publications or GitHub repos showcasing your skills

Education

Annual budget for your tech/gadgets needs
Generous Referral Bonuses

Responsibilities

*AI/ML Engineer,
you will collaborate with a cross-functional data team comprising of DevSecOps engineers, Product Owners, Data Engineers and Data Scientists. Your primary responsibility will be to develop machine learning models that are integral to a larger pipeline delivering value to our end customers.

View full posting on CareerOneStop → ID: 846be6e0254d

Machine Learning Engineer, AWS Applied AI Solution

Amazon · Seattle, WA

Mid-level Bachelor's

2026-05-27

WA 2026-05-27

Requirements

3+ years of non-internship professional software development experience
2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
1+ years of software development engineer or related occupational experience
1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
1+ years of Object Oriented Design experience
Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
Experience programming with at least one software programming language

Preferred

3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Bachelor's degree in computer science or equivalent

Responsibilities

Work closely with Applied Scientists and cross-functional engineering teams to transform research code into robust, scalable production systems
Own end-to-end deployment at scale of Generative AI and ML methods, ensuring reliability and performance
Establish scalable, efficient, automated processes for large-scale data analysis, machine learning model development, model validation and serving
Research and implement innovative approaches for efficient model deployment, training, and optimization
Document processes and methods for both technical and non-technical audiences, ensuring knowledge transfer and best practices
Contribute to code reviews and maintain high engineering standards across the team
Mentor junior MLEs and actively participate in recruiting top talent to grow
Present outcomes and explain technical approaches to senior leadership, translating complex concepts into business impact

View full posting on CareerOneStop → ID: bad8b55da3c4

Senior Product Data Scientist Manager, Android

Google · Kirkland, WA

Manager Master's

2026-05-27

WA 2026-05-27

Requirements

Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
13 years of work experience using analytics to solv.e product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 10 years work experience and a Master's degree)
5 years of experience as a people manager within a technical leadership role.

Preferred

Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
15 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
6 years of experience as a people manager within a technical leadership role.

Responsibilities

Android, Business, and Communications (ABC) is at the core of how people and businesses connect across the globe. Our mission is to build the world's most helpful, expressive, and secure communication experiences. With communication apps such as Google Messages and Dialer, we ship products that make a meaningful difference in billions of lives worldwide.
We define standard-setting "toothbrush journeys"-from fundamental calling reliability to high-resolution media sharing and expressive reactions. Beyond peer-to-peer connection, we are pioneering the next generation of conversational commerce, enabling businesses to deliver app-like experiences directly within the messaging interface. Whether adapting mobile features for a multi-device world on Wear OS or driving engagement with features like call screen, we focus on high-impact innovation that connects everyone, regardless of their device.
The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.
The US base salary range for this full-time position is $240,000-$334,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Direct projects that combine analytical and organizational complexity towards clear, sound, and actionable decisions.
Own projects end-to-end, covering problem definition, metrics development, data extraction and manipulation, visualization, creation, implementation of analytical/statistical models, and presentation to stakeholders.
Address ambiguous or new problems by using the capabilities of existing systems and collaborate to turn broad problems into work for the team.
Oversee the integration of cross-functional and cross-organizational project/process timelines, drive improvements and recommendations, and define operational goals and objectives.
Lead a team of data scientists, oversee technical accuracy across the organization, provide essential technical oversight for ranking, personalization, and classification strategies to scale the business globally.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: c1b62ce0b414

Staff Machine Learning Engineer, Search Ranking

Snap Inc. · Bellevue, WA

Senior Doctorate

2026-05-27

WA 2026-05-27

Requirements

Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
8+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 7+ year of post-grad machine learning experience; or PhD in a relevant technical field + 4 years of post-grad machine learning experience
Experience developing machine learning models for relevance ranking, personalization, intent understanding, and/or engagement optimization

Preferred

Advanced degree in Computer Science, Machine Learning, Statistics, Mathematics, Information Retrieval, or a related field
Direct experience building Search ranking systems, including query understanding, retrieval, ranking, re-ranking, relevance modeling, or result blending
Experience with ads ranking, recommendation ranking, feed ranking, marketplace ranking, or content discovery systems
Experience with learning-to-rank methods such as LambdaMART, pairwise/listwise ranking losses, neural ranking models, or transformer-based rankers
Experience with candidate generation, retrieval models, ANN search, embeddings, vector search, or two-stage ranking architectures
Experience optimizing ranking systems for multiple objectives, including relevance, engagement, quality, diversity, freshness, long-term user value, and monetization
Experience with LLMs, foundation models, semantic search, natural language understanding, or retrieval-augmented generation
Experience building low-latency ML serving systems and improving production model reliability
Track record of publishing, patenting, or otherwise advancing the state of the art in search, ranking, recommendations, ads, or applied ML

Responsibilities

Lead the design and development of machine learning models for Search ranking, including relevance ranking, personalization, result quality, intent understanding, and engagement optimization
Own major ranking initiatives from problem definition through experimentation, launch, and iteration
Develop and improve ranking models using techniques such as learning-to-rank, deep retrieval, neural ranking, sequence models, embeddings, multi-task learning, calibrated prediction, and large-scale feature engineering
Build ranking systems that balance multiple objectives, such as relevance, user satisfaction, freshness, diversity, fairness, safety, latency, and business goals
Partner with product managers, data scientists, and engineers to define success metrics, experimentation strategy, and long-term ranking roadmap
Analyze user behavior, search logs, query-result interactions, and model performance to identify opportunities for improvement
Design robust offline evaluation, online experimentation, and model monitoring frameworks
Improve feature pipelines, training infrastructure, serving systems, and model iteration velocity
Provide technical leadership across teams, influence architecture decisions, and mentor engineers working on ML ranking systems
Stay current with advances in search, recommendation systems, ads ranking, generative AI, LLM-based ranking, and retrieval-augmented systems
Knowledge, Skills, & Abilities
Strong machine learning fundamentals, including supervised learning, ranking models, embeddings, deep learning, optimization, evaluation, and experimentation
Strong programming skills in Python, C++, Java, Scala, or similar languages
Experience with large-scale data processing and ML infrastructure, such as Spark, Flink, Beam, TensorFlow, PyTorch, JAX, or similar tools
Ability to take ML models from research or prototyping into large-scale production systems
Strong understanding of online experimentation, A/B testing, metric design, model debugging, and tradeoff analysis
Proven ability to lead complex technical projects across multiple teams
Excellent communication skills and ability to explain complex ML concepts to technical and non-technical stakeholders

View full posting on CareerOneStop → ID: f5c9ea7fb7cc

Staff Machine Learning Engineer, Search Ranking

Snap Inc. · Seattle, WA

Senior Doctorate

2026-05-27

WA 2026-05-27

Requirements

Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
8+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 7+ year of post-grad machine learning experience; or PhD in a relevant technical field + 4 years of post-grad machine learning experience
Experience developing machine learning models for relevance ranking, personalization, intent understanding, and/or engagement optimization

Preferred

Advanced degree in Computer Science, Machine Learning, Statistics, Mathematics, Information Retrieval, or a related field
Direct experience building Search ranking systems, including query understanding, retrieval, ranking, re-ranking, relevance modeling, or result blending
Experience with ads ranking, recommendation ranking, feed ranking, marketplace ranking, or content discovery systems
Experience with learning-to-rank methods such as LambdaMART, pairwise/listwise ranking losses, neural ranking models, or transformer-based rankers
Experience with candidate generation, retrieval models, ANN search, embeddings, vector search, or two-stage ranking architectures
Experience optimizing ranking systems for multiple objectives, including relevance, engagement, quality, diversity, freshness, long-term user value, and monetization
Experience with LLMs, foundation models, semantic search, natural language understanding, or retrieval-augmented generation
Experience building low-latency ML serving systems and improving production model reliability
Track record of publishing, patenting, or otherwise advancing the state of the art in search, ranking, recommendations, ads, or applied ML

Responsibilities

Lead the design and development of machine learning models for Search ranking, including relevance ranking, personalization, result quality, intent understanding, and engagement optimization
Own major ranking initiatives from problem definition through experimentation, launch, and iteration
Develop and improve ranking models using techniques such as learning-to-rank, deep retrieval, neural ranking, sequence models, embeddings, multi-task learning, calibrated prediction, and large-scale feature engineering
Build ranking systems that balance multiple objectives, such as relevance, user satisfaction, freshness, diversity, fairness, safety, latency, and business goals
Partner with product managers, data scientists, and engineers to define success metrics, experimentation strategy, and long-term ranking roadmap
Analyze user behavior, search logs, query-result interactions, and model performance to identify opportunities for improvement
Design robust offline evaluation, online experimentation, and model monitoring frameworks
Improve feature pipelines, training infrastructure, serving systems, and model iteration velocity
Provide technical leadership across teams, influence architecture decisions, and mentor engineers working on ML ranking systems
Stay current with advances in search, recommendation systems, ads ranking, generative AI, LLM-based ranking, and retrieval-augmented systems
Knowledge, Skills, & Abilities
Strong machine learning fundamentals, including supervised learning, ranking models, embeddings, deep learning, optimization, evaluation, and experimentation
Strong programming skills in Python, C++, Java, Scala, or similar languages
Experience with large-scale data processing and ML infrastructure, such as Spark, Flink, Beam, TensorFlow, PyTorch, JAX, or similar tools
Ability to take ML models from research or prototyping into large-scale production systems
Strong understanding of online experimentation, A/B testing, metric design, model debugging, and tradeoff analysis
Proven ability to lead complex technical projects across multiple teams
Excellent communication skills and ability to explain complex ML concepts to technical and non-technical stakeholders

View full posting on CareerOneStop → ID: fd5ea7bbecae

Data Scientist, Product

OpenAI Inc. · Seattle, WA

Mid-level

2026-05-25

WA 2026-05-25

Responsibilities

As a Data Scientist on the Applied Product team, you will contribute to a data-driven product development culture for consumer and enterprise products at OpenAI. This is critical as our products reach millions of users and businesses worldwide. We are focused on aligning both research and product development to drive measurable impact for these individuals and organizations alike.
You should expect to define our north-star metrics, design A/B tests, and establish source-of-truth dashboards that the entire company can use to answer their own product questions. Most importantly, you should expect to be a core member of the product development team.
This role is based in San Francisco, CA or Seattle, WA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
*In this role, you will:
Embed with the product development team as a trusted partner, uncovering new ways to improve the product and drive growth
Define and interpret A/B tests that help answer critical questions about the impact of model and UX changes to our product
Establish a data-driven product development culture by defining, tracking, and operationalizing feature-, product-, and company-level metrics
Develop and socialize dashboards, reports, and other ways of enabling the team and company to answer product data questions in a self-serve way
*You might thrive in this role if you have:
5+ years experience in a quantitative role navigating highly ambiguous environments, ideally as an early data scientist or product analyst at a hyper-growth product company or research org
Proposed, designed, and run rigorous experiments with clear insights and product recommendations utilizing SQL and Python
Defined, implemented, and operationalized new feature and product-level metrics from scratch
Excellent communication skills with demonstrated ability to communicate with product managers, engineers, and executives alike
Strategic insights beyond the paradigm of statistical significance testing
*You could be an especially great fit if you have:
Strong programming background, with ability to run simulations and prototype variants
Experience validating quantitative insights with qualitative methods (e.g. surveys, UXR)
Demonstrated prior experience in NLP, large language models, or generative AI

View full posting on CareerOneStop → ID: 382a92856766

Data Scientist- Sr. Consultant level

Visa Usa Inc · Bellevue, WA

Senior

2026-05-25

WA 2026-05-25

Responsibilities

The Visa Acceptance Platform is the foundation for creating innovative payment solutions that drive exceptional customer experience. It lets you easily leverage a broad range of pre-integrated modular services and a growing ecosystem of technology and payments partners. Because it's Visa, the platform is secure, robust, and resilient. And because it's open, it will continue evolving to support you into the future.
At Visa, we believe AI technologies have the potential to radically transform commerce. We launchedVisa Intelligent Commerce to enable this next era of commerce. This program provides the infrastructure and tools developers need to build trusted, agentic experiences.
Make an impact with a purpose-driven industry leader. Join us today and be part of AI transformation journey at Visa.
We are looking for a versatile, curious, and energetic Senior Data Scientist to join our team of passionate and dedicated data scientists and engineers. We are the backbone for innovative data science and artificial intelligence developments at Visa acceptance, and we thrive on solving complex challenges on a global scale! As a Senior Data Scientist, you will be an integral part of a multi-functional development team inventing, designing, building, and testing products that reach a truly global customer base.
You will face big challenges and question the status quo, changing the way data products are developed at Visa! Come join us and see your efforts shape the digital future of payments.
The focus is on defining, executing, and delivering product and technical features at scale quickly and promoting a diverse culture of cross-functional collaboration and engineering excellence. Be an idea leader and bring industry best practices to benefit the team and the wider organization. The ability to balance demanding business capabilities with building for operational excellence while meeting regulatory, security and privacy requirements.
Ability to quickly grasp and evaluate new ideas and technologies from internal and external sources. Lead/Influence multiple teams, matching them with appropriate technology and business problems while building a culture of both innovation and drive for excellence.
Transform our digital offerings by leveraging AI to enhance our current product line and develop exciting new products targeting our banking, fintech and integration partners, which will enable the next wave of innovation in payments. We need a strong technology leader, who is an expert in data science, agile delivery, building purpose driven teams, and has a background in complex integration projects. Prior experience in payments, or a background in building high volume transaction and data processing systems is preferred.
Provides technical expertise and mentors others to implement extensible, maintainable, and reusable data models and strategies and adheres to all security and privacy requirements for the application of artificial intelligence and data science.
Develops strategies for and leads team's efforts to drive efficiencies across data extraction and ensure data quality and completeness using data wrangling, complex data mo

View full posting on CareerOneStop → ID: 42aa4220e35c

Lead Data Scientist

Visa Usa Inc · Bellevue, WA

Senior

2026-05-25

WA 2026-05-25

Responsibilities

The Visa Acceptance Platform is the foundation for creating innovative payment solutions that drive exceptional customer experience. It lets you easily leverage a broad range of pre-integrated modular services and a growing ecosystem of technology and payments partners. Because it's Visa, the platform is secure, robust, and resilient. And because it's open, it will continue evolving to support you into the future.
At Visa, we believe AI technologies have the potential to radically transform commerce. We launched Visa Intelligent Commerce to enable this next era of commerce. This program provides the infrastructure and tools developers need to build trusted, agentic experiences.
Make an impact with a purpose-driven industry leader. Join us today and be part of AI transformation journey at Visa.
We are looking for a versatile, curious, and energetic Lead Data Scientist to join our team of passionate and dedicated engineers. We are the backbone for innovative data science and artificial intelligence developments at Visa acceptance, and we thrive on solving complex challenges on a global scale! As a Lead Data Scientist, you will be an integral part of a multi-functional development team inventing, designing, building, and testing products that reach a truly global customer base.
You will face big challenges and question the status quo, changing the way data products are developed at Visa! Come join us and see your efforts shape the digital future of payments.
The focus is on defining, executing, and delivering product and technical features at scale quickly and promoting a diverse culture of cross-functional collaboration and engineering excellence. Be an idea leader and bring industry best practices to benefit the team and the wider organization. The ability to balance demanding business capabilities with building for operational excellence while meeting regulatory, security and privacy requirements.
The successful candidate will be comfortable navigating the challenging dynamic payments space and leading global teams responsible for platform transformation efforts. This candidate will play a pivotal role in our continued embrace of AI, seeking new paths to revenue by improving delivery efficiency and pushing forward for new products.
Provides technical expertise and mentors others to implement extensible, maintainable, and reusable code, defines framework, principles, coding patterns, guidelines, styles, and standard methodologies, and adheres to all security requirements for the application of artificial intelligence and data science.
Develops strategies for and leads team's efforts to drive efficiencies across data extraction and ensure data quality and completeness using data wrangling, complex data modeling, and artificial intelligence.
Ensures adherence to data management principles, governance, process, and tools to maintain data quality across products.
Advises on technical specifications during discussions with collaborators (e.g., Product owners, business partners, Cybersecurity) to identify and clarify sophisticated technical or business requirements and identify business needs and upstream and/or downstream

View full posting on CareerOneStop → ID: edca5d9efec7

Sr Data Scientist

T-Mobile USA, Inc · Bellevue, WA

Senior

2026-05-24

WA 2026-05-24

At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual

View full posting on CareerOneStop → ID: 94ba14c706ca

Data Science Manager, Gen AI - SFL Scientific

Deloitte · Seattle, WA

Manager Doctorate

2026-05-23

WA 2026-05-23

Requirements

Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
6+ years of experience working in data science, data engineering, software engineering, or MLOps
6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
6+ years of experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms
4+ years of experience managing teams and delivering complex and critical projects
Live within commuting distance to one of Deloitte's consulting offices
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Limited immigration sponsorship may be available

Preferred

Experience with cloud deployment (AWS, Azure, GCP), such as building and scaling in AWS SageMaker or Azure ML Studio
Experience with developing and testing GenAI solutions
Experience in a client-facing role or internal AI product development role
Highly proficient written and verbal skills to support briefings, proposals, technical sprint plans, solution reports, progress updates, and executive presentations
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: b49278c50cf0

Data Scientist

Actalent · Seattle, WA

Mid-level Doctorate

2026-05-23

WA 2026-05-23

Requirements

Hands-on expertise with cutting-edge molecular biology, microbiology, and/or biochemistry methods and concepts.
Familiarity with data analysis tools and methodologies commonly used in modern laboratory data analysis.
5+ years of experience as a data scientist or in a similar role involving data extraction, analysis, statistical modeling, and communication.
5+ years of experience with data querying languages such as SQL.
5+ years of experience with scripting languages such as Python.
5+ years of experience with statistical or mathematical software such as R, SAS, or MATLAB.
Experience with statistical models, including multinomial logistic regression.
Experience building and working with data pipelines.
Demonstrated ability to work successfully within an entrepreneurial environment.
Excellent organizational skills with strong attention to detail and meticulous record keeping.
Strong verbal and written communication skills for technical and non-technical audiences.
Knowledge of safety procedures related to operation of laboratory equipment and handling of chemical and biological hazards.
Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or a Bachelor's degree with 8+ years of professional or military experience.

Preferred

PhD degree in a life science discipline such as Biochemistry, Genetics, Molecular Biology, or Microbiology, with 8-10 years of directly related commercial experience.
Ability to work effectively within multidisciplinary teams at the interface of life science and computer science.
Broad familiarity with different areas of the life sciences and their experimental approaches.
Hands-on experience in high-throughput research, including operation of liquid handling systems.
2+ years of experience with data visualization tools such as AWS QuickSight, Tableau, or R Shiny.
Experience using AWS and related cloud-based tools in support of data pipelines and analytics.
Experience serving as a leader and mentor on a data science team, supporting the development of colleagues' technical and analytical skills.

Responsibilities

Execute existing laboratory workflows from experimental planning through data analysis, ensuring accuracy, reproducibility, and timely completion of work.
Recognize, document, and escalate protocol deviations to relevant stakeholders, and contribute to corrective and preventive actions.
Ensure laboratory equipment and instruments remain in good operating condition, identify malfunctions, and perform or coordinate troubleshooting as needed.
Maintain an up-to-date understanding of laboratory methods, protocols, and analytical techniques used in the lab.
Provide structured feedback on laboratory workflows and participate in developing solutions to process bottlenecks, throughput limitations, and data quality issues.
Work with a team of researchers to extend, refine, and interpret advanced analytical methodologies in the life sciences.
Facilitate effective interactions with internal and external collaborators to improve efficiency and implementation of cutting-edge analytical methods.
Adapt to unexpected schedule changes and respond to urgent or emergency situations in the laboratory environment as needed.
Extract, clean, and analyze complex datasets using data querying and scripting languages, and build statistical models to support scientific and business decisions.
Develop, implement, and maintain robust data pipelines that support laboratory workflows and analytical processes.
Apply statistical and machine learning models, such as multinomial logistic regression, to derive insights from experimental and operational data.
Create clear, insightful visualizations and reports using data visualization tools to communicate findings to technical and non-technical stakeholders.
Communicate results, methods, and recommendations clearly in both written and verbal form, tailoring the level of detail to the audience.
Act as a leader and mentor within the data science function, guiding colleagues on best practices in data extraction, analysis, modeling, and communication.
Ensure adherence to laboratory safety procedures, including proper operation of laboratory equipment and safe handling of chemical and biological hazards.

View full posting on CareerOneStop → ID: c817b8fb9e7f

Data Scientist III

Indeed · Seattle, WA

Mid-level Doctorate

2026-05-23

WA 2026-05-23

Responsibilities

As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
Translate data into actionable insights to guide product, marketing and business decisions.
Develop and maintain scalable, robust data pipelines and models for large-scale product data. Collaborate with engineering and product teams to integrate data science solutions into product workflows.
Mentor and support other data scientists, promoting knowledge sharing and best practices.
Contribute to the development of AI agents and skills, methodologies, and processes that improve the efficiency and impact of the data science team.
Communicate findings clearly through presentations, visualizations, and documentation for diverse audiences.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
Expertise in A/B testing and experimentation is required
Solid foundation in data science methods and technologies.
Able to influence technical direction and contribute to long-term planning.
Able to work effectively with other teams and mentor colleagues.
Focused on delivering high-quality, impactful solutions that contribute to business goals.
Excellent written and verbal communication in English, effective with technical and business audiences.

View full posting on CareerOneStop → ID: 01370a76aa69

Data Scientist III - AMZ9442729

Amazon · Seattle, WA

Mid-level Bachelor's

2026-05-23

WA 2026-05-23

Requirements

Bachelor's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science or a related field and two years of experience in the job offered or a related occupation. Employer will accept four years of experience as equivalent to the Bachelor's degree and two years of experience. Must have one year of experience in the following skills: (1) building statistical models and machine learning models using large datasets from multiple resources; (2) building complex data analyses by leveraging scripting languages including Python, Java, or related scripting language; and (3) communicating with users, technical teams, and management to collect requirements, evaluate alternatives, and develop processes and tools to support the organization.

Preferred

Please see job description and the position requirements above.

Responsibilities

Own the data science elements of various products to help with data-based decision making, product performance optimization, and product performance tracking. Work directly with product managers to help drive the design of the product. Work with Technical Product Managers to help drive the build planning. Translate business problems and products into data requirements and metrics. Initiate the design, development, and implementation of scientific analysis projects or deliverables. Own the analysis, modelling, system design, and development of data science solutions for products. Write documents and make presentations that explain model/analysis results to the business. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches. Build consensus on data, metrics, and analysis to drive business and system strategy.

View full posting on CareerOneStop → ID: b84a4680a0d4

Principal Data Scientist

Microsoft Corporation · Redmond, WA

Senior Doctorate

2026-05-23

WA 2026-05-23

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.
*Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:

Preferred

6+ years of experience in at least one of programming languages like Python/C#/Java.
Great organizational, analytical, data science skills and intuition.
Fantastic problem solver: ability to solve problems that the world has not solved before.
Interpersonal skills: cross-group and cross-culture collaboration.
Experience with real world system building and data collection, including design, coding and evaluation.
Excellent communication to be able to communicate insights to senior leaders.
Experience with driving large collaboration across multiple teams.
Experience with communicating with different audiences to provide insights.
Demonstrated experience in applying statistics, experimentation and metrics to generate clear actionable insights.

Responsibilities

Leadership: Mentor data scientists to drive Microsoft Content product analysis and provide insights. At the same time, drive the AI Agents into Data Analysis to improve efficiency and enable data analysis for people with limited data knowledge.
Collaboration: Partner closely with Microsoft Content Dev/PM Team and data scientists from other Product (Edge, Copilot, Ads and Search.)
Data Strategy & Execution: Develop Agent for data analysis across Microsoft Content Org. Provide daily analysis, including standardized data collection, analysis, reporting, and interpretation; validate analytical approaches and results.
Advanced Analytics & Measurement: Apply LLM based AI skills, statistical modeling, data mining, and experimentation to large datasets; define and deliver metrics that accurately measure user and business.
Experimental Design & Implementation: Design and execute experiments across user and demand dimensions; translate strategy into clear, actionable, and measurable plans, sharing progress and results with stakeholders.
Influence & Decision-Making: Engage stakeholders with clear, compelling, and actionable insights; make independent decisions for the team and handle complex tradeoffs to drive product and service improvements.
Technical & Operational Leadership: Develop and standardize AI Agents for data analysis across the whole Microsoft Content and expand to other Product Org.
Standards & Trusted Advisory: Establish and uphold standards, policies, and best practices for high-quality, efficient, and extensible code; influence business, customer, and solution strategy with a solid customer focus; act as a trusted advisor.

View full posting on CareerOneStop → ID: b57bc9840952

Senior Applied Scientist, Kuiper Data Science Platform

Amazon · Redmond, WA

Senior Doctorate

2026-05-23

WA 2026-05-23

Requirements

Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
3+ years of building machine learning models for business application experience
PhD, or Master's degree and 6+ years of applied research experience
Experience programming in Java, C++, Python or related language
Experience with neural deep learning methods and machine learning

Preferred

Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
Experience with large scale distributed systems such as Hadoop, Spark etc.

Responsibilities

The position requires hands-on expertise in Analytics to identify and isolate issues, Statistical Modeling and traditional Machine Learning, the ability to write queries to aid in data extraction, and the ability to productionalize models. This role is a self sufficient scientist that can source data, build and evaluate models, and ultimately take those models and rules to deployment. You should have excellent communication skills and be able to work with stakeholders at all levels. Above all you should be a passionate, hard-working and creative person who loves creating business impact, loves solving difficult problems and doesn't mind getting involved in the details.
At Kuiper Data Science Platform team, you will collaborate with a diverse group of internal stakeholders, including fraud operations, Engineering teams, and the Data Platform, to identify and address fraud vulnerabilities. You will have the opportunity to develop rules and ML models to prevent Customer Terminal (CT) usage fraud and abuse. Your role will also allow you to leverage your customer-obsession skills by thoughtfully considering the user experience and ensuring it is not adversely affected by the mechanisms you design. If you are passionate about working with large-scale data, we offer ample opportunities to do so.

View full posting on CareerOneStop → ID: 84797e494dd4

Senior Data Scientist - SFL Scientific

Deloitte · Seattle, WA

Senior Doctorate

2026-05-23

WA 2026-05-23

Requirements

Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
3+ years of experience in AI/ML algorithm development using core data science languages and frameworks (Python, PyTorch, etc.) and data analysis (NLP, time-series analysis, computer vision)
3+ years of experience and a proven track record applying traditional ML and deep learning techniques (CNNs, RNNs, GANs) across real-world projects, including model tuning and performance validation in production environments
3+ years of experience deploying and optimizing ML models using tools like Kubernetes, Docker, TensorRT/Trion, RAPIDs, Kubeflow, and MLflow
3+ years of experience in leveraging cloud environments (AWS, Azure, or GCP) to deploy AI/ML workloads
Live within commuting distance to one of Deloitte's consulting offices
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Limited immigration sponsorship may be available

Preferred

2+ years of experience working in a client-facing, consulting environment
2+ years of experience leading project/client engagement teams in the execution of complex AI data science solutions
1+ year of experience with LLM/GenAI use cases and developing RAG solutions, tools, and services (i.e., LangChain, LangGraph, MCP, etc.)
1+ year of experience with AWS Sagemaker or AWS ML Studio
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $128,000 to $252,500.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: 786722d6ad58

Data Science Manager, Gen AI - SFL Scientific

Deloitte · Portland, OR

Manager Doctorate

2026-05-23

WA 2026-05-23

Requirements

Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
6+ years of experience working in data science, data engineering, software engineering, or MLOps
6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
6+ years of experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms
4+ years of experience managing teams and delivering complex and critical projects
Live within commuting distance to one of Deloitte's consulting offices
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Limited immigration sponsorship may be available

Preferred

Experience with cloud deployment (AWS, Azure, GCP), such as building and scaling in AWS SageMaker or Azure ML Studio
Experience with developing and testing GenAI solutions
Experience in a client-facing role or internal AI product development role
Highly proficient written and verbal skills to support briefings, proposals, technical sprint plans, solution reports, progress updates, and executive presentations
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: 51a9883c9b6b

Data Scientist III

Indeed · Portland, OR

Mid-level Doctorate

2026-05-23

WA 2026-05-23

Responsibilities

As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
Translate data into actionable insights to guide product, marketing and business decisions.
Develop and maintain scalable, robust data pipelines and models for large-scale product data. Collaborate with engineering and product teams to integrate data science solutions into product workflows.
Mentor and support other data scientists, promoting knowledge sharing and best practices.
Contribute to the development of AI agents and skills, methodologies, and processes that improve the efficiency and impact of the data science team.
Communicate findings clearly through presentations, visualizations, and documentation for diverse audiences.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
Expertise in A/B testing and experimentation is required
Solid foundation in data science methods and technologies.
Able to influence technical direction and contribute to long-term planning.
Able to work effectively with other teams and mentor colleagues.
Focused on delivering high-quality, impactful solutions that contribute to business goals.
Excellent written and verbal communication in English, effective with technical and business audiences.

View full posting on CareerOneStop → ID: fb37eb36abff

Senior Data Scientist - SFL Scientific

Deloitte · Portland, OR

Senior Doctorate

2026-05-23

WA 2026-05-23

Requirements

Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
3+ years of experience in AI/ML algorithm development using core data science languages and frameworks (Python, PyTorch, etc.) and data analysis (NLP, time-series analysis, computer vision)
3+ years of experience and a proven track record applying traditional ML and deep learning techniques (CNNs, RNNs, GANs) across real-world projects, including model tuning and performance validation in production environments
3+ years of experience deploying and optimizing ML models using tools like Kubernetes, Docker, TensorRT/Trion, RAPIDs, Kubeflow, and MLflow
3+ years of experience in leveraging cloud environments (AWS, Azure, or GCP) to deploy AI/ML workloads
Live within commuting distance to one of Deloitte's consulting offices
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Limited immigration sponsorship may be available

Preferred

2+ years of experience working in a client-facing, consulting environment
2+ years of experience leading project/client engagement teams in the execution of complex AI data science solutions
1+ year of experience with LLM/GenAI use cases and developing RAG solutions, tools, and services (i.e., LangChain, LangGraph, MCP, etc.)
1+ year of experience with AWS Sagemaker or AWS ML Studio
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $128,000 to $252,500.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: dc907bbc0f93

Data Scientist -Project Delivery Senior Analyst - AI & Engineering

Deloitte · Boise, ID

Senior Bachelor's

2026-05-23

ID 2026-05-23

Requirements

4+ years of experience Proficiency with Python, statistical modeling, and machine learning frameworks (e.g. scikit-learn, PyTorch, TensorFlow).
4+ years of experience with feature engineering, model development, validation, and deployment.
4+ years of experience Understanding of MLOps pipelines, model versioning, monitoring, and retraining processes.
4+ years of experience Ability to translate complex business problems into analytical solutions with measurable outcomes.
4+ years of experience Strong knowledge of data wrangling, exploratory analysis, and visualization.
4+ years of experience Familiarity with cloud ML services (e.g. SageMaker, Azure ML, Fabric ML).
4+ years of experience communicating and explaining insights and model behavior to non-technical stakeholders
Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
Limited immigration sponsorship may be available
Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Analytical/ Decision Making Responsibilities
Analytical ability to manage multiple projects and prioritize tasks into manageable work products
Can operate independently or with minimum supervision
Excellent Written and Communication Skills
Ability to deliver technical demonstrations
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $72,900-$134,000

Responsibilities

The Data Scientist will analyze, cleanse, and model complex data to help organizations make better decisions and predict future trends.
Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.

View full posting on CareerOneStop → ID: 4fa3856975f3

Data Scientist III

Indeed · Boise, ID

Mid-level Doctorate

2026-05-23

ID 2026-05-23

Responsibilities

As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
Translate data into actionable insights to guide product, marketing and business decisions.
Develop and maintain scalable, robust data pipelines and models for large-scale product data. Collaborate with engineering and product teams to integrate data science solutions into product workflows.
Mentor and support other data scientists, promoting knowledge sharing and best practices.
Contribute to the development of AI agents and skills, methodologies, and processes that improve the efficiency and impact of the data science team.
Communicate findings clearly through presentations, visualizations, and documentation for diverse audiences.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
Expertise in A/B testing and experimentation is required
Solid foundation in data science methods and technologies.
Able to influence technical direction and contribute to long-term planning.
Able to work effectively with other teams and mentor colleagues.
Focused on delivering high-quality, impactful solutions that contribute to business goals.
Excellent written and verbal communication in English, effective with technical and business audiences.

View full posting on CareerOneStop → ID: cb8be40266ce

Data Scientist III

Indeed · Helena, MT

Mid-level Doctorate

2026-05-23

MT 2026-05-23

Responsibilities

As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
Translate data into actionable insights to guide product, marketing and business decisions.
Develop and maintain scalable, robust data pipelines and models for large-scale product data. Collaborate with engineering and product teams to integrate data science solutions into product workflows.
Mentor and support other data scientists, promoting knowledge sharing and best practices.
Contribute to the development of AI agents and skills, methodologies, and processes that improve the efficiency and impact of the data science team.
Communicate findings clearly through presentations, visualizations, and documentation for diverse audiences.
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
Expertise in A/B testing and experimentation is required
Solid foundation in data science methods and technologies.
Able to influence technical direction and contribute to long-term planning.
Able to work effectively with other teams and mentor colleagues.
Focused on delivering high-quality, impactful solutions that contribute to business goals.
Excellent written and verbal communication in English, effective with technical and business audiences.

View full posting on CareerOneStop → ID: 46eaf2e8109e

Data Scientist III - AMZ9442729

AMAZON.COM SERVICES LLC · Seattle, WA

Mid-level Bachelor's

2026-05-23

WA 2026-05-23

Requirements

Bachelor's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science or a related field and two years of experience in the job offered or a related occupation. Employer will accept four years of experience as equivalent to the Bachelor's degree and two years of experience. Must have one year of experience in the following skills: (1) building statistical models and machine learning models using large datasets from multiple resources; (2) building complex data analyses by leveraging scripting languages including Python, Java, or related scripting language; and (3) communicating with users, technical teams, and management to collect requirements, evaluate alternatives, and develop processes and tools to support the organization.

Responsibilities

Own the data science elements of various products to help with data-based decision making, product performance optimization, and product performance tracking. Work directly with product managers to help drive the design of the product. Work with Technical Product Managers to help drive the build planning. Translate business problems and products into data requirements and metrics. Initiate the design, development, and implementation of scientific analysis projects or deliverables. Own the analysis, modelling, system design, and development of data science solutions for products. Write documents and make presentations that explain model/analysis results to the business. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches. Build consensus on data, metrics, and analysis to drive business and system strategy.

View full posting on CareerOneStop → ID: 443c7d8f5701

Data Scientists - Finance

T-Mobile USA, Inc · Bellevue, WA

Mid-level Master's

2026-05-23

WA 2026-05-23

Requirements

(1) Applying statistical and mathematical methodologies including Linear Regression, Logistic Regression, Decision Tree, Cluster Analysis, and Hypothesis Testing to perform segmentation, prediction, forecast, and exploratory analysis;
(2) Extracting, integrating, and processing large-scale structured and unstructured datasets from multiple enterprise data warehouses and transactional databases using advanced SQL, Python and SAS. Performing data integrity checks to ensure completeness and accuracy under SOX compliance framework;
(3) Building and refining financial models to estimate the ASC 820 or IFRS 13 fair value of various assets and liabilities using US GAAP and IFRS compliant approaches by synthesizing data from internal systems, third-party market data, and historical financial performance;
(4) Performing fair value estimates of assets and liabilities using IFRS 13, IFRS 15, ASC460, ASC 606, ASC820, and ASC 805; and
(5) Interpreting and translating the results of statistical and mathematical methodologies including Linear Regression, Logistic Regression, Decision Tree, Cluster Analysis, and Hypothesis Testing and accounting fair value estimates using ASC 460, ASC 606, ASC 820, and ASC 805 prepared by the data scientist into actionable insights for accounting leadership.

Education

PRIMARY REQUIREMENTS: Master's degree in Measurement and Statistics, Applied Statistics, Financial Engineering, or related, and 1 year of relevant work experience.
ALTERNATIVE REQUIREMENTS: Bachelor's degree in Measurement and Statistics, Applied Statistics, Financial Engineering, or related, and 3 years of relevant work experience.
Location: Bellevue, WA
This position is eligible for the employee re

Responsibilities

Operate the model, coordinate with stake holders, and run a process to estimate the liability associated with the Jump Program.
Update the Jump liability program to increase efficiency for various stakeholders.
Provide adhoc analytics on various valuations.
Perform data analytics and statistical analysis to support forecast of device values.
Provide data analytics and statistical analysis to support the estimate of the Apple Forever Liability.
Work with various stakeholders to prepare a model to forecast credit losses on T-Mobile service contracts.
Understand key data architecture and changes to the company to provide insights to various stakeholders with respect to data and valuation estimates.
Telecommuting is permitted, but applicant must work from the worksite location at least 3-4 days per week.
Minimal amount of travel for training or conferences may be required periodically.

View full posting on CareerOneStop → ID: 558f8db1e0a6

Staff Machine Learning Engineer, Ads Measurement Products

Pinterest, Inc. · Seattle, WA

Senior

2026-05-23

WA 2026-05-23

Requirements

7+ years of experience building and deploying large-scale ML systems in production, ideally in ads, measurement, recommendation, ranking, search, or closely related domains.
Degree in Computer Science, Statistics, Engineering, or a related technical field, or equivalent experience.
Meaningful hands-on experience in ads measurement, ad effectiveness, or incrementality domains, such as conversion lift, brand lift, budget-split testing, matched-market tests, MMM, MTA, conversion APIs, or clean-

Responsibilities

Lead the design, implementation, and productionization of ML-powered components for ads measurement products, including areas such as measurement methodologies, diagnostics, anomaly detection, automated insight generation, and advertiser decision-support.
Build and evolve scalable ML and data pipelines that support first- and third-party measurement products, partnering with infrastructure and product engineering teams to create reliable, maintainable, and performant systems.
Partner closely with Data Science to translate causal inference, incrementality, and experimentation methodologies into production-grade systems and tools that increase the speed, scale, and usability of measurement products without compromising rigor.
Collaborate with internal and external measurement partners, such as clean rooms, conversion APIs, MMM partners, and MTA vendors, to integrate high-quality signals and develop joint measurement solutions.
Establish ML engineering best practices across data quality, feature pipelines, evaluation, experimentation, monitoring, and model governance within Measurement Products, and mentor engineers and partner teams working on ML-powered components.
Influence the Ads Product and Engineering roadmap by identifying high-leverage opportunities to apply ML to measurement workflows and products, and by driving clear technical trade-offs, interfaces, and success metrics across teams.
Use AI to accelerate development, prototyping, analysis, and iteration, while applying strong judgment, testing, and verification to ensure correctness, explainability, data protection, and advertiser trust.

View full posting on CareerOneStop → ID: c9f67b6fd413

Staff Machine Learning Engineer, Programmatic Ads

Pinterest, Inc. · Seattle, WA

Senior

2026-05-23

WA 2026-05-23

Requirements

Industry experience building and shipping large-scale production ML systems in ads, search, recommendations, or related domains.
Deep experience with control/optimization algorithms for bidding, pacing, allocation, or similar marketplace problems.
Strength in probabilistic modeling and measurement (e.g., quality/fraud signals, deep-learning engagement prediction) and making principled trade-offs between coverage, accuracy, and impact.
Proven Staff-level technical leadership as an IC: driving technical direction and cross-team alignment without formal people management.
Demonstrated ability to use AI to improve speed and quality of your workflow, with a strong track record of validating and stress-testing AI-assisted outputs.
Degree in Computer Science, Statistics, or a related field.
Experience with Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.
Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.
We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to

Responsibilities

Design and implement algorithms for real-time bidding, ad scoring/ranking, inventory selection, and yield optimization across multiple exchanges.
Own end-to-end ML systems: problem framing, metrics, data/feature design, model training, evaluation, and online experimentation.
Introduce and productionize new exchange and supply signals (e.g., quality, conversions, identity, fraud, content understanding) to unlock incremental advertiser value.
Partner closely with Ads Ranking & Bidding, Measurement, and Programmatic Engineering to integrate new models and objectives into the ads stack.
Use AI to accelerate analysis, experimentation, and iteration (e.g., exploring model variants, automating path from learnings to launch) while applying strong judgment and vision.

View full posting on CareerOneStop → ID: 35410b55f160

Sr. Data Scientist - Industrial Industry Focused

Cutsforth, LLC · Ferndale, WA

Senior

2026-05-23

WA 2026-05-23

Responsibilities

We are building the intelligence layer for industrial operations -- transforming raw sensor telemetry, time-series data, and field equipment signals into predictive diagnostics that keep critical assets running.
As a Data Scientist on our team, you will work at the intersection of time-series analytics, machine learning, and engineering domain-knowledge, turning field equipment sensor data, time-series telemetry, and operational data into actionable insights -- designing and deploying production-grade solutions for predictive maintenance and anomaly detection across our customers' industrial environments.
You will partner directly with engineering, product, and domain experts to translate business and operational challenges into scalable, production-ready data science solutions that drive measurable impact on reliability, efficiency, and revenue -- with direct visibility into how your work reduces downtime and keeps critical operations running.
We actively support team members to publish, present, and contribute to the industrial AI community.
Design, develop, train, and deploy machine learning and AI models that process and analyze field equipment sensor data (time-series IoT, embedded device telemetry) alongside structured and unstructured datasets.

View full posting on CareerOneStop → ID: 298868e59769

AI/ML Engineer - Higher Ed

Cengage Group · Seattle, WA

Mid-level Bachelor's

2026-05-22

WA 2026-05-22

Requirements

Bachelor's degree in Computer Science, Engineering, or related field
4+ years of experience in software engineering, with at least 2 years focused on AI/ML
Strong proficiency in Python with experience building production ML or LLM systems
Hands-on experience with modern AI APIs (OpenAI, Anthropic, AWS Bedrock)
Experience with RAG architectures, vector databases, and embedding models
Solid software engineering fundamentals including testing, CI/CD, and system design
Experience shipping production features at scale (thousands or millions of users)
Strong communication skills to work with product, design, and research partners

Preferred

Experience in EdTech or adjacent domains with production education AI features
Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI)
Background in learning science, educational psychology, or instructional design
Experience with FERPA compliance and education-industry data handling
Familiarity with accessibility standards (WCAG, Section 508, DOJ accessibility)
Experience with fine-tuning, LoRA, or custom model training
*Tools & Technologies
You should be comfortable with many of the following:
Languages: Python, JavaScript/TypeScript, SQL
AI/ML: OpenAI API, Anthropic API, AWS Bedrock, LangChain, LlamaIndex, Hugging Face
Vector DBs: Pinecone, Weaviate, pgvector, Chroma
Cloud: AWS (Lambda, ECS, SageMaker, Bedrock), Azure OpenAI
Data: Snowflake, Databricks, Postgres, Redis
DevOps: Docker, Terraform, GitHub Actions, CI/CD pipelines
*Key Competencies
Shipping Mindset - delivers features weekly, not quarterly
Technical Craft - writes clean, tested, production-grade code
Learning Orientation - cares about whether AI actually improves learning outcomes
Systems Thinking - sees the full platform and integrates AI cleanly
Collaboration - partners effectively with product, design, research, and platform engineering
Continuous Improvement - iterates on models and features based on data

Responsibilities

*HED AI Feature Development
Ship and improve AI features weekly across Cengage HED platforms
Build and integrate Student Assistant capabilities including tutoring, hinting, and feedback
Develop Instructor Insight Assistant features for course analytics and at-risk student identification
Create Content Studio capabilities for AI-assisted content authoring and adaptation
Integrate LLMs, RAG systems, and agentic workflows into HED platform architectures
*Platform Integration & Engineering
Integrate AI features into existing HED platform architectures and data systems
Partner with platform engineering on API design, scaling, and production deployment
Build retrieval systems against Cengage's proprietary content library (books, assessments, media)
Ensure AI features meet FERPA compliance and accessibility standards (WCAG, DOJ)
Resolve technical blockers and production issues with urgency
*Measurement & Optimization
Monitor feature usage, engagement, and learning outcome impact
Track and improve model performance on quality, cost, and latency dimensions
Partner with learning scientists and researchers on efficacy measurement
Iterate rapidly based on student feedback, instructor feedback, and usage telemetry
Maintain documentation and engineering runbooks for deployed AI features

View full posting on CareerOneStop → ID: de5d6ba5cd8f

Data Science Manager, PXT Central Science

Amazon · Seattle, WA

Manager Master's

2026-05-22

WA 2026-05-22

Requirements

5+ years of building quantitative solutions as a scientist or science manager experience
2+ years of scientists or machine learning engineers management experience
5+ years of applying statistical models for large-scale application and building automated analytical systems experience
Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
Knowledge of Python or R or other scripting language

Preferred

Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems

Responsibilities

Leadership & Team Management: Independently manage and develop a diverse science team, creating an environment that enables consistent delivery and innovation; Build and maintain a high-performing team that can operate effectively and autonomously; Drive strategic growth opportunities for team members, providing paths to demonstrate higher-level scope, impact, and leadership; Establish clear performance metrics and audit mechanisms to track and communicate team progress; Foster a team culture focused on bringing research to production and delivering customer value
Technical & Scientific Direction: Partner with stakeholders and leadership to define and execute the scientific vision for your team; Lead the development of structural and predictive models, leveraging emerging technologies and novel features; Drive the implementation of data science workflows and simulation frameworks; Bridge the gap between science, technology, and business requirements; Leverage the broader Amazon scientific community to enhance team capabilities and knowledge sharing
Strategic Planning & Execution: Define and maintain team structure, strategic direction, and owned technologies; Establish processes that enable consistent delivery and quality of scientific artifacts; Drive reasonable schedules and adjust priorities to ensure optimal outcomes; Create and implement audit mechanisms to track team performance against goals; Remove roadblocks and optimize team productivity
Communication & Influence: Create well-written documents to effectively communicate with technical and non-technical audiences; Influence science and analytics practices across the organization; Build strong partnerships with stakeholders across different business units; Present complex scientific findings to senior leadership; Drive adoption of best practices and innovative solutions

View full posting on CareerOneStop → ID: 343cbeff7e60

Data Science Manager, PXT Central Science

Amazon · Bellevue, WA

Manager Master's

2026-05-22

WA 2026-05-22

Requirements

5+ years of building quantitative solutions as a scientist or science manager experience
2+ years of scientists or machine learning engineers management experience
5+ years of applying statistical models for large-scale application and building automated analytical systems experience
Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
Knowledge of Python or R or other scripting language

Preferred

Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems

Responsibilities

Leadership & Team Management: Independently manage and develop a diverse science team, creating an environment that enables consistent delivery and innovation; Build and maintain a high-performing team that can operate effectively and autonomously; Drive strategic growth opportunities for team members, providing paths to demonstrate higher-level scope, impact, and leadership; Establish clear performance metrics and audit mechanisms to track and communicate team progress; Foster a team culture focused on bringing research to production and delivering customer value
Technical & Scientific Direction: Partner with stakeholders and leadership to define and execute the scientific vision for your team; Lead the development of structural and predictive models, leveraging emerging technologies and novel features; Drive the implementation of data science workflows and simulation frameworks; Bridge the gap between science, technology, and business requirements; Leverage the broader Amazon scientific community to enhance team capabilities and knowledge sharing
Strategic Planning & Execution: Define and maintain team structure, strategic direction, and owned technologies; Establish processes that enable consistent delivery and quality of scientific artifacts; Drive reasonable schedules and adjust priorities to ensure optimal outcomes; Create and implement audit mechanisms to track team performance against goals; Remove roadblocks and optimize team productivity
Communication & Influence: Create well-written documents to effectively communicate with technical and non-technical audiences; Influence science and analytics practices across the organization; Build strong partnerships with stakeholders across different business units; Present complex scientific findings to senior leadership; Drive adoption of best practices and innovative solutions

View full posting on CareerOneStop → ID: c4a3c0ed4ac4

Data Scientist

ManpowerGroup · Redmond, WA

Mid-level

2026-05-22

WA 2026-05-22

View full posting on CareerOneStop → ID: b8680b5649b6

Machine Learning Engineer

Zoom · Seattle, WA

Mid-level Master's

2026-05-22

WA 2026-05-22

Responsibilities

Design, implement, and optimize GenAI algorithms, techniques and solutions to address complex
business challenges.
Collaborate with cross-functional teams to integrate research findings into scalable engineering solutions that align with business objectives.
Participate in code reviews, design discussions, and technical presentations to ensure the quality and reliability of our engineering solutions.
Identify opportunities for improvement in existing systems and proposing innovative solutions to enhance performance, scalability, and reliability.
Stay up to date with the newest developments in GenAI research and engineering to continuously improve our technical capabilities.
What we're looking for:
Requires a Bachelor's degree in Computer Science, Computer Engineering, a related field, or a foreign degree equivalent. Must have 3 years of experience in job offered or related occupation. Must have 3 years of experience in the following skills:
Utilizing one or more programming languages such as Python, C, C++, or CUDA in building scalable software systems;
Deep learning frameworks including PyTorch and TensorFlow;
Presenting academic or personal AI projects;
Collaborating with cross-functional teams to present technical concepts to both technical and nontechnical audiences;
Agentic AI including LLM driven AI agents, agentic RAG;
Building scalable, maintainable, and production-ready machine learning systems; and
Analyzing data and troubleshooting issues related to deployed AI systems.
Telecommuting work arrangement permitted one day per week. Four days in office required. Position does not require domestic or international travel.
In Lieu of a Bachelor's degree and 3 years of experience the company will accept the following: Must have Master's degree in Computer Science, Computer Engineering, a related field, or a foreign degree equivalent. Must have 1 years of experience in job offered or related occupation. Must have 1 years of experience in the following skills:

View full posting on CareerOneStop → ID: e5af510de9ba

Senior Consultant - Data Science / Data Lake

Deloitte · Seattle, WA

Senior Bachelor's

2026-05-22

WA 2026-05-22

Requirements

3+ years of experience in analytics consulting, cybersecurity analytics, security operations, or a combination of these
2+ years of experience with artificial intelligence development tools or frameworks such as vector databases, LangChain, or CrewAI
2+ years of experience using Python, Structured Query Language (SQL), R, or SAS to prepare data for analysis, engineer features, visualize data, or support machine learning workflows
Experience working with cyber security cloud platforms such as Google SecOps, Amazon Web Services (AWS), or Microsoft Azure, and exposure to security operations center (SOC) threat hunting or incident response
Bachelor's degree in Engineering, Mathematics, Statistics, Computer Science, Cybersecurity, or a field aligned to the role; or 4 years of equivalent professional experience
Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
Limited immigration sponsorship may be available.

Preferred

Experience supporting the design, development, or deployment of enterprise data science or artificial intelligence solutions
Experience applying artificial intelligence, machine learning, or advanced data engineering to cybersecurity use cases such as detection engineering or threat response acceleration
Experience parsing and normalizing cyber or information technology telemetry datasets
Experience with PyTorch, Keras, TensorFlow, Scikit-learn, NumPy, or SciPy
Experience with Apache Kafka, Storm, or Spark
Experience creating client-ready materials using Microsoft PowerPoint or Microsoft Visio
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: 05bde5bca4e7

Senior Data Scientist, Special Projects

Amazon · Seattle, WA

Senior Doctorate

2026-05-22

WA 2026-05-22

Requirements

5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Experience in applying statistical models for large-scale application and building automated analytical systems

Preferred

PhD in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning approaches and algorithms
Experience in a ML or data scientist role with a large technology company
5+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

Work hands-on with complex, noisy datasets to derive actionable insights and explain/debug black-box models using interpretability and data-attribution methods (e.g., SHAP/TreeSHAP, Anchors, Integrated Gradients, counterfactuals, nearest-neighbor exemplars, influence/data attribution).
Design and analyze experiments and observational studies with rigorous statistical inference, including confidence intervals, power/sample-size estimation, variance reduction, and appropriate tests (e.g., two-sample tests, permutation tests, sequential testing, and multiple-comparison control such as FDR).
Benchmark models and datasets using classical and modern techniques; select ML methods based on data and operational constraints (e.g., clustering/KDE, tree ensembles, CNN/RNN/Transformers, representation learning), and evaluate with robust metrics and diagnostics (e.g., AUROC, AUPRG, proper scoring rules/losses, calibration/ECE, threshold/utility curves, slice-based evaluation, and error analysis).
Apply production-grade measurement and MLOps practices, including data quality monitoring, drift/shift detection (PSI, KS, MMD/embedding drift), and A/B test design and readouts with disciplined diagnosis of metric movement (e.g., instrumentation changes, seasonality, novelty effects, sample-ratio mismatch, guardrail tradeoffs).
Deliver end-to-end analyses that improve team execution and decision-making-define goal-driving metrics with stakeholders, build clear reporting (tables, dashboards, and visualizations), and communicate results that translate into concrete actions.
Investigate anomalies and data integrity issues across diverse data sources using structured root-cause analysis, correlation diagnostics, significance testing, and simulation across high- and low-fidelity datasets.
Partner closely with cross-functional domain experts to design experiments and interpret results, applying modern statistical methods to evaluate predictive and generative models as well as operational and process performance.
Develop production-quality analytics and modeling code-write well-tested, maintainable SQL/Python scripts and analysis workflows that can be promoted into production pipelines, and continuously adopt new statistical methods and best practices as the field evolves.
New data has just landed and promoted to our datalake. You load the data and verify it's overall integrity by visualizing variation across target subsets. You realize we may have made progress toward our goals and begin to test the validity of your nominal results. At midday you grab lunch with new coworkers and learn about their fields or weird interests (there are many). You generate visualizations for the entire dataset and perform significance tests that reinforce specific findings. You meet with peers in the afternoon to discuss your findings and breakdown the remaining tasks to finalize your group report!

View full posting on CareerOneStop → ID: b43894514d0e

Senior Data Scientist, Customer Care

GoTo · Olympia, WA

Senior

2026-05-22

WA 2026-05-22

View full posting on CareerOneStop → ID: f47e33d9113b

AI/ML Engineer - Higher Ed

Cengage Group · Portland, OR

Mid-level Bachelor's

2026-05-22

WA 2026-05-22

Requirements

Bachelor's degree in Computer Science, Engineering, or related field
4+ years of experience in software engineering, with at least 2 years focused on AI/ML
Strong proficiency in Python with experience building production ML or LLM systems
Hands-on experience with modern AI APIs (OpenAI, Anthropic, AWS Bedrock)
Experience with RAG architectures, vector databases, and embedding models
Solid software engineering fundamentals including testing, CI/CD, and system design
Experience shipping production features at scale (thousands or millions of users)
Strong communication skills to work with product, design, and research partners

Preferred

Experience in EdTech or adjacent domains with production education AI features
Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI)
Background in learning science, educational psychology, or instructional design
Experience with FERPA compliance and education-industry data handling
Familiarity with accessibility standards (WCAG, Section 508, DOJ accessibility)
Experience with fine-tuning, LoRA, or custom model training
*Tools & Technologies
You should be comfortable with many of the following:
Languages: Python, JavaScript/TypeScript, SQL
AI/ML: OpenAI API, Anthropic API, AWS Bedrock, LangChain, LlamaIndex, Hugging Face
Vector DBs: Pinecone, Weaviate, pgvector, Chroma
Cloud: AWS (Lambda, ECS, SageMaker, Bedrock), Azure OpenAI
Data: Snowflake, Databricks, Postgres, Redis
DevOps: Docker, Terraform, GitHub Actions, CI/CD pipelines
*Key Competencies
Shipping Mindset - delivers features weekly, not quarterly
Technical Craft - writes clean, tested, production-grade code
Learning Orientation - cares about whether AI actually improves learning outcomes
Systems Thinking - sees the full platform and integrates AI cleanly
Collaboration - partners effectively with product, design, research, and platform engineering
Continuous Improvement - iterates on models and features based on data

Responsibilities

*HED AI Feature Development
Ship and improve AI features weekly across Cengage HED platforms
Build and integrate Student Assistant capabilities including tutoring, hinting, and feedback
Develop Instructor Insight Assistant features for course analytics and at-risk student identification
Create Content Studio capabilities for AI-assisted content authoring and adaptation
Integrate LLMs, RAG systems, and agentic workflows into HED platform architectures
*Platform Integration & Engineering
Integrate AI features into existing HED platform architectures and data systems
Partner with platform engineering on API design, scaling, and production deployment
Build retrieval systems against Cengage's proprietary content library (books, assessments, media)
Ensure AI features meet FERPA compliance and accessibility standards (WCAG, DOJ)
Resolve technical blockers and production issues with urgency
*Measurement & Optimization
Monitor feature usage, engagement, and learning outcome impact
Track and improve model performance on quality, cost, and latency dimensions
Partner with learning scientists and researchers on efficacy measurement
Iterate rapidly based on student feedback, instructor feedback, and usage telemetry
Maintain documentation and engineering runbooks for deployed AI features

View full posting on CareerOneStop → ID: d044f0171ecc

AI/ML Engineer - Higher Ed

Cengage Group · Boise, ID

Mid-level Bachelor's

2026-05-22

ID 2026-05-22

Requirements

Bachelor's degree in Computer Science, Engineering, or related field
4+ years of experience in software engineering, with at least 2 years focused on AI/ML
Strong proficiency in Python with experience building production ML or LLM systems
Hands-on experience with modern AI APIs (OpenAI, Anthropic, AWS Bedrock)
Experience with RAG architectures, vector databases, and embedding models
Solid software engineering fundamentals including testing, CI/CD, and system design
Experience shipping production features at scale (thousands or millions of users)
Strong communication skills to work with product, design, and research partners

Preferred

Experience in EdTech or adjacent domains with production education AI features
Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI)
Background in learning science, educational psychology, or instructional design
Experience with FERPA compliance and education-industry data handling
Familiarity with accessibility standards (WCAG, Section 508, DOJ accessibility)
Experience with fine-tuning, LoRA, or custom model training
*Tools & Technologies
You should be comfortable with many of the following:
Languages: Python, JavaScript/TypeScript, SQL
AI/ML: OpenAI API, Anthropic API, AWS Bedrock, LangChain, LlamaIndex, Hugging Face
Vector DBs: Pinecone, Weaviate, pgvector, Chroma
Cloud: AWS (Lambda, ECS, SageMaker, Bedrock), Azure OpenAI
Data: Snowflake, Databricks, Postgres, Redis
DevOps: Docker, Terraform, GitHub Actions, CI/CD pipelines
*Key Competencies
Shipping Mindset - delivers features weekly, not quarterly
Technical Craft - writes clean, tested, production-grade code
Learning Orientation - cares about whether AI actually improves learning outcomes
Systems Thinking - sees the full platform and integrates AI cleanly
Collaboration - partners effectively with product, design, research, and platform engineering
Continuous Improvement - iterates on models and features based on data

Responsibilities

*HED AI Feature Development
Ship and improve AI features weekly across Cengage HED platforms
Build and integrate Student Assistant capabilities including tutoring, hinting, and feedback
Develop Instructor Insight Assistant features for course analytics and at-risk student identification
Create Content Studio capabilities for AI-assisted content authoring and adaptation
Integrate LLMs, RAG systems, and agentic workflows into HED platform architectures
*Platform Integration & Engineering
Integrate AI features into existing HED platform architectures and data systems
Partner with platform engineering on API design, scaling, and production deployment
Build retrieval systems against Cengage's proprietary content library (books, assessments, media)
Ensure AI features meet FERPA compliance and accessibility standards (WCAG, DOJ)
Resolve technical blockers and production issues with urgency
*Measurement & Optimization
Monitor feature usage, engagement, and learning outcome impact
Track and improve model performance on quality, cost, and latency dimensions
Partner with learning scientists and researchers on efficacy measurement
Iterate rapidly based on student feedback, instructor feedback, and usage telemetry
Maintain documentation and engineering runbooks for deployed AI features

View full posting on CareerOneStop → ID: 8f1d85c81181

Senior Data Scientist, Customer Care

GoTo · Boise, ID

Senior

2026-05-22

ID 2026-05-22

View full posting on CareerOneStop → ID: c1638f2eb280

Senior Data Scientist, Customer Care

GoTo · Helena, MT

Senior

2026-05-22

MT 2026-05-22

View full posting on CareerOneStop → ID: 505b80b1db92

Senior Data Scientist, Customer Care

GoTo · Salem, OR

Senior

2026-05-22

OR 2026-05-22

View full posting on CareerOneStop → ID: dfef397eda8b

AI/ML Engineer - Higher Ed

Cengage Group · Billings, MT

Mid-level

2026-05-22

MT 2026-05-22

View full posting on CareerOneStop → ID: 7f0adaaeae32

Data Scientist - 3035128

Apex Systems, Inc. · Redmond, WA

Mid-level

2026-05-22

WA 2026-05-22

View full posting on CareerOneStop → ID: b40da831182f

Data Scientists - Finance

T-Mobile USA, Inc. · Bellevue, WA

Mid-level

2026-05-22

WA 2026-05-22

View full posting on CareerOneStop → ID: c52ca62f36b0

Principal Data Scientist

Microsoft Corporation · Redmond, WA

Senior

2026-05-22

WA 2026-05-22

View full posting on CareerOneStop → ID: d6c33f0eced7

Staff Machine Learning Engineer

Micron Technology, Inc. · Boise, ID

Senior

2026-05-22

ID 2026-05-22

View full posting on CareerOneStop → ID: 4cd0a8314408

Data Scientist

TEKsystems · Seattle, WA

Mid-level

2026-05-21

WA 2026-05-21

Requirements

3-5+ years of data science or analytics experience
Strong SQL and Python skills
Experience with experimentation (A/B testing), hypothesis testing, or causal analysis
Experience working with data pipelines and large-scale datasets
Ability to drive business or product decisions using data

Preferred

Forecasting or time series experience
Product analytics or customer behavior analysis
Experience with cloud or modern data tools (e.g., Snowflake, Databricks)
Exposure to NLP, LLMs, or unstructured data analysis
Technical Skills
Python, SQL, Data Analysis, Experimentation, Predictive Modeling

Responsibilities

Design and analyze experiments (A/B testing) to evaluate product features
Build and maintain data pipelines to support experimentation, analytics, and scalable product insights
Develop predictive models to understand user behavior and system performance
Translate data findings into actionable insights that directly influence product and engineering decisions
Perform analysis using SQL and Python on large datasets
Partner cross-functionally to define metrics and measure impact

View full posting on CareerOneStop → ID: bd47e3f27cd5

Data Scientist - Senior Manager- Consulting - Location OPEN

EY · Seattle, WA

Manager Doctorate

2026-05-21

WA 2026-05-21

Requirements

PhD preferred in Computer Science, Machine Learning, Computational Linguistics, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Master's with exceptional applied experience also considered.
12+ years of applied data science / ML experience, with at least 3 years in a senior technical leadership role.
Demonstrable experience taking AI and ML systems from prototype to production - across multiple problem types (e.g., predictive modeling, NLP, retrieval / RAG, optimization, or agentic workflows).
Hands-on proficiency in Python and the modern ML/AI stack (PyTorch, Hugging Face, scikit-learn, and at least one of LangChain / LangGraph or an equivalent agent / LLM framework).
Practical experience with at least one major cloud AI platform (Vertex AI, Bedrock, Azure AI Foundry, Databricks Mosaic AI) and one vector / retrieval stack.
Experience designing evaluation frameworks for AI systems - beyond standard benchmarks - including evaluation for foundation-model-based or agentic workflows.
Experience operating in a client-facing or cross-functional environment, translating business problems into rigorous data-science programs.
*Ideally, you will also have
Published research or open-source contributions in AI / ML agentic systems, retrieval, memory and grounding, knowledge graphs, foundation models, optimization, or related areas.
Experience with knowledge graphs, ontologies, and neuro-symbolic approaches to grounding and reasoning.
Experience building or contributing to a cognitive harness, agent operating system, or agent runtime - internal or open source.
Experience with continual learning, online evaluation, drift detection, and model / memory monitoring in production.
Familiarity with regulated-industry constraints (SOX, HIPAA, GDPR) and how AI design interacts with audit, retention, and explainability.
Prior consulting, product, or hyperscaler experience - comfortable in a fast, ambiguous environment with senior stakeholders.
*What we look fo
We are looking for a data-science leader who is genuinely excited about hard technical problems and who is as comfortable in a research paper as in a production codebase. You should be the kind of person who treats AI systems as engineered products designed, evaluated, and operated with rigor and who wants to lead a team that ships to Fortune 500 clients across multiple industries.

Responsibilities

As a Senior Manager, Data Scientist, you will be a hands-on technical leader who shapes the data-science agenda across multiple workstreams. You will own technical direction, experimentation, and the path from prototype to production for the problems you take on. You will be expected to build, not just design and to lift the bar of the team around you.
Lead data-science strategy and execution across multiple AI workstreams including agentic AI, the cognitive harness, memory and grounding, foundation-model applications, machine learning, optimization, and applied analytics.
Drive the applied-research and experimentation agenda long-context vs. retrieval trade-offs, hybrid search, reranking, evaluation design, model selection, fine-tuning, and emerging techniques as the field evolves.
Design and contribute to the build of core platform components including elements of EY's cognitive harness (memory services, retrieval pipelines, grounding layers, evaluation harnesses) and other reusable AI capabilities.
Establish evaluation and quality frameworks for AI systems retrieval and grounding fidelity, hallucination rate, model accuracy, latency, cost, fairness, and continuous evaluation in production.
Lead and mentor data scientists and ML engineers set the technical bar, run design reviews, and grow rigor in experimentation, model selection, and production readiness.
Partner with sector and functional teams (Finance, Risk, Tax, Supply Chain, HR, Operations) to translate business problems into rigorous, deliverable data-science programs.
Engage with clients on complex AI problems shape the technical approach, defend it in front of senior stakeholders, and own delivery quality.
Stay abreast of AI technology trends and provide directional guidance and recommendations around models, frameworks, tools, and patterns that fit our clients' existing ecosystems.
Apply combined business and technical knowledge to develop and execute target architectures that enable implementation, monitoring, and ongoing improvement of AI at scale.
*Skills and attributes for success
This role will work to deliver tech at speed, innovate at scale, and put humans at the center. You will provide technical guidance and share knowledge with team members with diverse skills and backgrounds. You will consistently deliver quality client services, focusing on more complex, judgmental, and specialized issues surrounding modern AI, foundation models, and emerging technology. You will demonstrate deep technical capabilities and professional knowledge, and you will lead through making.
Strong, hands-on data scientist who codes comfortable building and shipping models, pipelines, services, and experimental frameworks, not just specifying them.
Deep technical breadth across modern AI foundation models and prompting, retrieval and grounding, embeddings and fine-tuning, classical ML, optimization, and experimentation rigor.
Working knowledge of agentic systems and cognitive harness / agent-runtime architectures - memory, tools, policies, evaluation, observability, cost and the trade-offs between them.
Familiarity with at least one major agent SDK (Google ADK, AWS Bedrock AgentCore, LangGraph, AutoGen, OpenAI Agents SDK) and the ability to compare them critically.
Experience designing and operating production AI systems on cloud platforms (GCP, AWS, Azure, Databricks) including responsible-AI guardrails, monitoring, and continuous evaluation.
Track record of leading data-science teams across multiple projects setting technical strategy, mentoring, and raising the bar on rigor and delivery quality.
Excellent communication skills able to explain complex AI concepts to executive clients, and able to defend technical choices in front of architects, engineers, and researchers.
Comfortable moving between problem spaces - equally credible designing a memory architecture, evaluating a forecasting model, or shaping a new agentic workflow.

View full posting on CareerOneStop → ID: d4ce7ce958d6

Machine Learning Engineer - LLM Evaluation & Automation

TEKsystems · Seattle, WA

Mid-level

2026-05-21

WA 2026-05-21

Requirements

5+ years of experience in ML engineering, NLP, or AI/ML automation
Strong programming skills in Python and SQL
Deep understanding of machine learning concepts with a focus on NLP and advanced LLM capabilities (e.g., Chain-of-Thought, agentic workflows)
Experience working with large-scale datasets and data pipelines
Strong experience with LLM evaluation, prompt engineering, or auto grading systems
Experience developing metrics and KPIs to measure model output quality and consistency

Preferred

Experience with LLM-as-judge systems or human + model evaluation frameworks
Background in inter-rater reliability, evaluation calibration, or judged systems design
Experience with PySpark or distributed data processing tools
Exposure to building dashboards or visualization tools for model performance tracking
Technical Skills
Python, SQL, NLP, LLM Evaluation, Prompt Engineering, Machine Learning, Data Pipelines, Automation Systems
NOTE: This posting is for an existing vacancy. ?
We reserve the right to pay above or below the posted wage based on factors unrelated to sex, race, or any other protected
classification. Eligibility requirements apply to some benefits
and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. This temporary role may be eligible for the following:
Medical, dental & vision
Insurance (Basic/Supplemental Life & AD&D)

Responsibilities

Design and build LLM-based evaluation frameworks, including automated scoring pipelines and rubric-based grading systems
Build and maintain data pipelines for evaluation datasets using Python, SQL, and scalable processing tools
Translate complex evaluation results into clear, actionable insights for technical and non-technical stakeholders
Implement automation workflows and agentic evaluation systems to improve efficiency and reduce manual efforts
Develop prompt engineering strategies to evaluate output quality, accuracy, and consistency
Create and maintain metrics, KPIs, and dashboards to track and communicate model performance
Conduct error analysis, root-cause investigations, and quality deep dives to guide model improvements
Partner cross-functionally to define evaluation methodologies and integrate them into production workflows

View full posting on CareerOneStop → ID: c794d9571b4c

Data Scientist - Senior Manager- Consulting - Location OPEN

EY · Olympia, WA

Manager Doctorate

2026-05-21

WA 2026-05-21

Requirements

PhD preferred in Computer Science, Machine Learning, Computational Linguistics, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Master's with exceptional applied experience also considered.
12+ years of applied data science / ML experience, with at least 3 years in a senior technical leadership role.
Demonstrable experience taking AI and ML systems from prototype to production - across multiple problem types (e.g., predictive modeling, NLP, retrieval / RAG, optimization, or agentic workflows).
Hands-on proficiency in Python and the modern ML/AI stack (PyTorch, Hugging Face, scikit-learn, and at least one of LangChain / LangGraph or an equivalent agent / LLM framework).
Practical experience with at least one major cloud AI platform (Vertex AI, Bedrock, Azure AI Foundry, Databricks Mosaic AI) and one vector / retrieval stack.
Experience designing evaluation frameworks for AI systems - beyond standard benchmarks - including evaluation for foundation-model-based or agentic workflows.
Experience operating in a client-facing or cross-functional environment, translating business problems into rigorous data-science programs.
*Ideally, you will also have
Published research or open-source contributions in AI / ML agentic systems, retrieval, memory and grounding, knowledge graphs, foundation models, optimization, or related areas.
Experience with knowledge graphs, ontologies, and neuro-symbolic approaches to grounding and reasoning.
Experience building or contributing to a cognitive harness, agent operating system, or agent runtime - internal or open source.
Experience with continual learning, online evaluation, drift detection, and model / memory monitoring in production.
Familiarity with regulated-industry constraints (SOX, HIPAA, GDPR) and how AI design interacts with audit, retention, and explainability.
Prior consulting, product, or hyperscaler experience - comfortable in a fast, ambiguous environment with senior stakeholders.
*What we look fo
We are looking for a data-science leader who is genuinely excited about hard technical problems and who is as comfortable in a research paper as in a production codebase. You should be the kind of person who treats AI systems as engineered products designed, evaluated, and operated with rigor and who wants to lead a team that ships to Fortune 500 clients across multiple industries.

Responsibilities

As a Senior Manager, Data Scientist, you will be a hands-on technical leader who shapes the data-science agenda across multiple workstreams. You will own technical direction, experimentation, and the path from prototype to production for the problems you take on. You will be expected to build, not just design and to lift the bar of the team around you.
Lead data-science strategy and execution across multiple AI workstreams including agentic AI, the cognitive harness, memory and grounding, foundation-model applications, machine learning, optimization, and applied analytics.
Drive the applied-research and experimentation agenda long-context vs. retrieval trade-offs, hybrid search, reranking, evaluation design, model selection, fine-tuning, and emerging techniques as the field evolves.
Design and contribute to the build of core platform components including elements of EY's cognitive harness (memory services, retrieval pipelines, grounding layers, evaluation harnesses) and other reusable AI capabilities.
Establish evaluation and quality frameworks for AI systems retrieval and grounding fidelity, hallucination rate, model accuracy, latency, cost, fairness, and continuous evaluation in production.
Lead and mentor data scientists and ML engineers set the technical bar, run design reviews, and grow rigor in experimentation, model selection, and production readiness.
Partner with sector and functional teams (Finance, Risk, Tax, Supply Chain, HR, Operations) to translate business problems into rigorous, deliverable data-science programs.
Engage with clients on complex AI problems shape the technical approach, defend it in front of senior stakeholders, and own delivery quality.
Stay abreast of AI technology trends and provide directional guidance and recommendations around models, frameworks, tools, and patterns that fit our clients' existing ecosystems.
Apply combined business and technical knowledge to develop and execute target architectures that enable implementation, monitoring, and ongoing improvement of AI at scale.
*Skills and attributes for success
This role will work to deliver tech at speed, innovate at scale, and put humans at the center. You will provide technical guidance and share knowledge with team members with diverse skills and backgrounds. You will consistently deliver quality client services, focusing on more complex, judgmental, and specialized issues surrounding modern AI, foundation models, and emerging technology. You will demonstrate deep technical capabilities and professional knowledge, and you will lead through making.
Strong, hands-on data scientist who codes comfortable building and shipping models, pipelines, services, and experimental frameworks, not just specifying them.
Deep technical breadth across modern AI foundation models and prompting, retrieval and grounding, embeddings and fine-tuning, classical ML, optimization, and experimentation rigor.
Working knowledge of agentic systems and cognitive harness / agent-runtime architectures - memory, tools, policies, evaluation, observability, cost and the trade-offs between them.
Familiarity with at least one major agent SDK (Google ADK, AWS Bedrock AgentCore, LangGraph, AutoGen, OpenAI Agents SDK) and the ability to compare them critically.
Experience designing and operating production AI systems on cloud platforms (GCP, AWS, Azure, Databricks) including responsible-AI guardrails, monitoring, and continuous evaluation.
Track record of leading data-science teams across multiple projects setting technical strategy, mentoring, and raising the bar on rigor and delivery quality.
Excellent communication skills able to explain complex AI concepts to executive clients, and able to defend technical choices in front of architects, engineers, and researchers.
Comfortable moving between problem spaces - equally credible designing a memory architecture, evaluating a forecasting model, or shaping a new agentic workflow.

View full posting on CareerOneStop → ID: 4f65551cb8e5

Data Scientist, Manufacturing Analytics

Ford Motor Company · Olympia, WA

Mid-level Doctorate

2026-05-21

WA 2026-05-21

Responsibilities

Accelerate the application of value-added analytics and machine learning into the portfolio of products for Manufacturing Analytics.
Drive analytic excellence into product teams by collaborating with Data Scientists, Data Engineers and Software Engineers in analytic and machine learning methods.
Work closely with the Product Manager and Product Owner to translate Business Value needs into analytic deliverables and, where appropriate, software products for delivery by product teams.
Work hands-on with the team and other partners to deliver solutions that meet our customer's requirements and needs.
Act as a consultant to the business vs. an order taker.
Balance "doing it right" with "speed to delivery" by identifying and mitigating risk, generating options, educating business and other decision makers, and taking on justified technical debt.
*You'll have...
Bachelor's degree in a quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics OR Computer Science
2+ year experience hands-on experience with mathematical programming, machine learning, artificial intelligence, optimization/simulation techniques, or statistical analysis
1+ year of experience delivering analytics solutions
1+ year experience with Agile team methodology
Demonstrated technical skills in data analytics, AI/ML, operations research, and/or optimization
*Even better, you may have...
Master's degree or PhD preferred in quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics, Computer Science, or related field
Knowledge and experience working with OGC and related teams/activities (e.g., Compliance, Litigation and Regulatory)
Proven experience with developing data products/solutions to support analytic applications in Ford's data ecosystem
Experience with Product Driven Operating Model or Agile Product Development Process
Proven proficiency in developing and deploying analytic models, working in a team environment, supporting customers and/or end users
Comfortable working in an environment where problems are not always well-defined
Strong interpersonal and leadership skills, with ability to communicate complex topics to leaders and peers in a simple and clear manne
Well-organized, independent, and ready to work with minimal supervision
Inquisitive, proactive, and interested in learning new tools and techniques
Demonstrated hands on experience with deploying data products and/or analytic models in Ford's on-prem and/or Google Cloud Platform
Demonstrated experience to translate real-world business problems into analytical formulations and interpreting analytics results with non-analytics business partners
Working knowledge of Manufacturing IT legacy systems such as FIS, Maximo, QLS, etc.
Thorough understanding of the 'Common Data Model' standard published by Manufacturing
Understanding of the IIoT Platform architecture including MQTT
You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder...or all of the above? No matter what you choose, we offer a work life that works for you, including:
Immediate medical, dental, vision and prescription drug coverage
Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
Vehicle discount program for employees and family members and management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service
A generous schedule of paid holidays, including the week between Christmas and New Year's Day
Paid time off and the option to purchase additional vacation time.
This position is a salary grade 5 - salary grade 8 and ranges from $68,300-$192,900.

View full posting on CareerOneStop → ID: aff447194327

Senior Data Scientist - Fleet Analytics

The Hertz Corporation · Olympia, WA

Senior Master's

2026-05-21

WA 2026-05-21

Requirements

3-5 years hands-on experience in a data scientist role
3+ years of data querying languages (e.g. SQL) and scripting languages (e.g. Python)
3+ years of end-to-end machine learning model development experience (e.g. problem statement definition, exploratory data analysis, feature engineering, model development / tuning, and deployment)
Demonstrated experience using machine learning to drive a business impact
Experience in a ML or data scientist role with car rental or technology company.
Bachelor or Masters degree in Computer Science, or other quantitative discipline such as statistics, mathematics, physics or engineering
*What You'll Get:
Up to 40% off any standard Hertz Rental??
Medical, Dental & Vision plan options
Retirement programs, including 401(k) employer matching
Paid Parental Leave & Adoption Assistance
Employee Assistance Program for employees & family
Educational Reimbursement & Discounts
Voluntary Insurance Programs - Pet, Legal/Identity Theft, Critical Illness
Perks & Discounts -Theme Park Tickets, Gym Discounts & more
The Hertz Corporation operates the Hertz, Dollar Car Rental, Thrifty Car Rental brands in approximately 9,700 corporate and franchisee locations throughout North America, Europe, The Caribbean, Latin America, Africa, the Middle East, Asia, Australia and New Zealand. The Hertz Corporation is one of the largest worldwide airport general use vehicle rental companies, and the Hertz brand is one of the most recognized in the world.

Responsibilities

At Hertz, we are at the forefront of innovation, leveraging cutting-edge technologies to build the best damage management technologies in the transportation industry. We want the brightest AI & ML minds to join our Damage Science Team to help us develop and/or maintain capabilities. Examples of projects the team work on include the below:L
Rationalize Repair Estimates and Invoices with Large Language Models (LLMs): Implement sophisticated LLMs to make intelligent repair routing decisions, ensuring repairs are conducted efficiently and cost-effectively.
Forecast Repair Needs: Develop models to predict future repair & maintenance needs based on historical data and trends.
Optimize Decision Making: Create models to determine if we should keep/sell/salvage a vehicle.
Demand Planning: Forecast customer demand at a given location at a given time.
*What You Will Do:
Formulate the strategic and tactical steps to carry out the model development lifecycle end-to-end (i.e. problem statement definition, exploratory data analysis, feature engineering, model development / tuning, and model implementation).
Build and maintain descriptive, predictive, and prescriptive models to measure the performance of the new products and services
Define and implement best practices to generate accurate analytics, reports, visualizations, and dashboards to explain results simply and succinctly to technical, non-technical, and senior management
Build partnerships and work cross-functionally to identify use cases and opportunities to enhance operational efficiency and drive business value through positive impact on OKRs.
Work with an owner mentality to drive business impact even if that means supporting pipeline creation or decision support analytics.

View full posting on CareerOneStop → ID: 286df7c97cda

Data Scientist - Senior Manager- Consulting - Location OPEN

EY · Portland, OR

Manager Doctorate

2026-05-21

WA 2026-05-21

Requirements

PhD preferred in Computer Science, Machine Learning, Computational Linguistics, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Master's with exceptional applied experience also considered.
12+ years of applied data science / ML experience, with at least 3 years in a senior technical leadership role.
Demonstrable experience taking AI and ML systems from prototype to production - across multiple problem types (e.g., predictive modeling, NLP, retrieval / RAG, optimization, or agentic workflows).
Hands-on proficiency in Python and the modern ML/AI stack (PyTorch, Hugging Face, scikit-learn, and at least one of LangChain / LangGraph or an equivalent agent / LLM framework).
Practical experience with at least one major cloud AI platform (Vertex AI, Bedrock, Azure AI Foundry, Databricks Mosaic AI) and one vector / retrieval stack.
Experience designing evaluation frameworks for AI systems - beyond standard benchmarks - including evaluation for foundation-model-based or agentic workflows.
Experience operating in a client-facing or cross-functional environment, translating business problems into rigorous data-science programs.
*Ideally, you will also have
Published research or open-source contributions in AI / ML agentic systems, retrieval, memory and grounding, knowledge graphs, foundation models, optimization, or related areas.
Experience with knowledge graphs, ontologies, and neuro-symbolic approaches to grounding and reasoning.
Experience building or contributing to a cognitive harness, agent operating system, or agent runtime - internal or open source.
Experience with continual learning, online evaluation, drift detection, and model / memory monitoring in production.
Familiarity with regulated-industry constraints (SOX, HIPAA, GDPR) and how AI design interacts with audit, retention, and explainability.
Prior consulting, product, or hyperscaler experience - comfortable in a fast, ambiguous environment with senior stakeholders.
*What we look fo
We are looking for a data-science leader who is genuinely excited about hard technical problems and who is as comfortable in a research paper as in a production codebase. You should be the kind of person who treats AI systems as engineered products designed, evaluated, and operated with rigor and who wants to lead a team that ships to Fortune 500 clients across multiple industries.

Responsibilities

As a Senior Manager, Data Scientist, you will be a hands-on technical leader who shapes the data-science agenda across multiple workstreams. You will own technical direction, experimentation, and the path from prototype to production for the problems you take on. You will be expected to build, not just design and to lift the bar of the team around you.
Lead data-science strategy and execution across multiple AI workstreams including agentic AI, the cognitive harness, memory and grounding, foundation-model applications, machine learning, optimization, and applied analytics.
Drive the applied-research and experimentation agenda long-context vs. retrieval trade-offs, hybrid search, reranking, evaluation design, model selection, fine-tuning, and emerging techniques as the field evolves.
Design and contribute to the build of core platform components including elements of EY's cognitive harness (memory services, retrieval pipelines, grounding layers, evaluation harnesses) and other reusable AI capabilities.
Establish evaluation and quality frameworks for AI systems retrieval and grounding fidelity, hallucination rate, model accuracy, latency, cost, fairness, and continuous evaluation in production.
Lead and mentor data scientists and ML engineers set the technical bar, run design reviews, and grow rigor in experimentation, model selection, and production readiness.
Partner with sector and functional teams (Finance, Risk, Tax, Supply Chain, HR, Operations) to translate business problems into rigorous, deliverable data-science programs.
Engage with clients on complex AI problems shape the technical approach, defend it in front of senior stakeholders, and own delivery quality.
Stay abreast of AI technology trends and provide directional guidance and recommendations around models, frameworks, tools, and patterns that fit our clients' existing ecosystems.
Apply combined business and technical knowledge to develop and execute target architectures that enable implementation, monitoring, and ongoing improvement of AI at scale.
*Skills and attributes for success
This role will work to deliver tech at speed, innovate at scale, and put humans at the center. You will provide technical guidance and share knowledge with team members with diverse skills and backgrounds. You will consistently deliver quality client services, focusing on more complex, judgmental, and specialized issues surrounding modern AI, foundation models, and emerging technology. You will demonstrate deep technical capabilities and professional knowledge, and you will lead through making.
Strong, hands-on data scientist who codes comfortable building and shipping models, pipelines, services, and experimental frameworks, not just specifying them.
Deep technical breadth across modern AI foundation models and prompting, retrieval and grounding, embeddings and fine-tuning, classical ML, optimization, and experimentation rigor.
Working knowledge of agentic systems and cognitive harness / agent-runtime architectures - memory, tools, policies, evaluation, observability, cost and the trade-offs between them.
Familiarity with at least one major agent SDK (Google ADK, AWS Bedrock AgentCore, LangGraph, AutoGen, OpenAI Agents SDK) and the ability to compare them critically.
Experience designing and operating production AI systems on cloud platforms (GCP, AWS, Azure, Databricks) including responsible-AI guardrails, monitoring, and continuous evaluation.
Track record of leading data-science teams across multiple projects setting technical strategy, mentoring, and raising the bar on rigor and delivery quality.
Excellent communication skills able to explain complex AI concepts to executive clients, and able to defend technical choices in front of architects, engineers, and researchers.
Comfortable moving between problem spaces - equally credible designing a memory architecture, evaluating a forecasting model, or shaping a new agentic workflow.

View full posting on CareerOneStop → ID: 06cb3337d70e

Senior Data Scientist - Fleet Analytics

The Hertz Corporation · Boise, ID

Senior Master's

2026-05-21

ID 2026-05-21

Requirements

3-5 years hands-on experience in a data scientist role
3+ years of data querying languages (e.g. SQL) and scripting languages (e.g. Python)
3+ years of end-to-end machine learning model development experience (e.g. problem statement definition, exploratory data analysis, feature engineering, model development / tuning, and deployment)
Demonstrated experience using machine learning to drive a business impact
Experience in a ML or data scientist role with car rental or technology company.
Bachelor or Masters degree in Computer Science, or other quantitative discipline such as statistics, mathematics, physics or engineering
*What You'll Get:
Up to 40% off any standard Hertz Rental??
Medical, Dental & Vision plan options
Retirement programs, including 401(k) employer matching
Paid Parental Leave & Adoption Assistance
Employee Assistance Program for employees & family
Educational Reimbursement & Discounts
Voluntary Insurance Programs - Pet, Legal/Identity Theft, Critical Illness
Perks & Discounts -Theme Park Tickets, Gym Discounts & more
The Hertz Corporation operates the Hertz, Dollar Car Rental, Thrifty Car Rental brands in approximately 9,700 corporate and franchisee locations throughout North America, Europe, The Caribbean, Latin America, Africa, the Middle East, Asia, Australia and New Zealand. The Hertz Corporation is one of the largest worldwide airport general use vehicle rental companies, and the Hertz brand is one of the most recognized in the world.

Responsibilities

At Hertz, we are at the forefront of innovation, leveraging cutting-edge technologies to build the best damage management technologies in the transportation industry. We want the brightest AI & ML minds to join our Damage Science Team to help us develop and/or maintain capabilities. Examples of projects the team work on include the below:L
Rationalize Repair Estimates and Invoices with Large Language Models (LLMs): Implement sophisticated LLMs to make intelligent repair routing decisions, ensuring repairs are conducted efficiently and cost-effectively.
Forecast Repair Needs: Develop models to predict future repair & maintenance needs based on historical data and trends.
Optimize Decision Making: Create models to determine if we should keep/sell/salvage a vehicle.
Demand Planning: Forecast customer demand at a given location at a given time.
*What You Will Do:
Formulate the strategic and tactical steps to carry out the model development lifecycle end-to-end (i.e. problem statement definition, exploratory data analysis, feature engineering, model development / tuning, and model implementation).
Build and maintain descriptive, predictive, and prescriptive models to measure the performance of the new products and services
Define and implement best practices to generate accurate analytics, reports, visualizations, and dashboards to explain results simply and succinctly to technical, non-technical, and senior management
Build partnerships and work cross-functionally to identify use cases and opportunities to enhance operational efficiency and drive business value through positive impact on OKRs.
Work with an owner mentality to drive business impact even if that means supporting pipeline creation or decision support analytics.

View full posting on CareerOneStop → ID: 6d1d2cdf3f61

Data Scientist - Senior Manager- Consulting - Location OPEN

EY · Salem, OR

Manager Doctorate

2026-05-21

OR 2026-05-21

Requirements

PhD preferred in Computer Science, Machine Learning, Computational Linguistics, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Master's with exceptional applied experience also considered.
12+ years of applied data science / ML experience, with at least 3 years in a senior technical leadership role.
Demonstrable experience taking AI and ML systems from prototype to production - across multiple problem types (e.g., predictive modeling, NLP, retrieval / RAG, optimization, or agentic workflows).
Hands-on proficiency in Python and the modern ML/AI stack (PyTorch, Hugging Face, scikit-learn, and at least one of LangChain / LangGraph or an equivalent agent / LLM framework).
Practical experience with at least one major cloud AI platform (Vertex AI, Bedrock, Azure AI Foundry, Databricks Mosaic AI) and one vector / retrieval stack.
Experience designing evaluation frameworks for AI systems - beyond standard benchmarks - including evaluation for foundation-model-based or agentic workflows.
Experience operating in a client-facing or cross-functional environment, translating business problems into rigorous data-science programs.
*Ideally, you will also have
Published research or open-source contributions in AI / ML agentic systems, retrieval, memory and grounding, knowledge graphs, foundation models, optimization, or related areas.
Experience with knowledge graphs, ontologies, and neuro-symbolic approaches to grounding and reasoning.
Experience building or contributing to a cognitive harness, agent operating system, or agent runtime - internal or open source.
Experience with continual learning, online evaluation, drift detection, and model / memory monitoring in production.
Familiarity with regulated-industry constraints (SOX, HIPAA, GDPR) and how AI design interacts with audit, retention, and explainability.
Prior consulting, product, or hyperscaler experience - comfortable in a fast, ambiguous environment with senior stakeholders.
*What we look fo
We are looking for a data-science leader who is genuinely excited about hard technical problems and who is as comfortable in a research paper as in a production codebase. You should be the kind of person who treats AI systems as engineered products designed, evaluated, and operated with rigor and who wants to lead a team that ships to Fortune 500 clients across multiple industries.

Responsibilities

As a Senior Manager, Data Scientist, you will be a hands-on technical leader who shapes the data-science agenda across multiple workstreams. You will own technical direction, experimentation, and the path from prototype to production for the problems you take on. You will be expected to build, not just design and to lift the bar of the team around you.
Lead data-science strategy and execution across multiple AI workstreams including agentic AI, the cognitive harness, memory and grounding, foundation-model applications, machine learning, optimization, and applied analytics.
Drive the applied-research and experimentation agenda long-context vs. retrieval trade-offs, hybrid search, reranking, evaluation design, model selection, fine-tuning, and emerging techniques as the field evolves.
Design and contribute to the build of core platform components including elements of EY's cognitive harness (memory services, retrieval pipelines, grounding layers, evaluation harnesses) and other reusable AI capabilities.
Establish evaluation and quality frameworks for AI systems retrieval and grounding fidelity, hallucination rate, model accuracy, latency, cost, fairness, and continuous evaluation in production.
Lead and mentor data scientists and ML engineers set the technical bar, run design reviews, and grow rigor in experimentation, model selection, and production readiness.
Partner with sector and functional teams (Finance, Risk, Tax, Supply Chain, HR, Operations) to translate business problems into rigorous, deliverable data-science programs.
Engage with clients on complex AI problems shape the technical approach, defend it in front of senior stakeholders, and own delivery quality.
Stay abreast of AI technology trends and provide directional guidance and recommendations around models, frameworks, tools, and patterns that fit our clients' existing ecosystems.
Apply combined business and technical knowledge to develop and execute target architectures that enable implementation, monitoring, and ongoing improvement of AI at scale.
*Skills and attributes for success
This role will work to deliver tech at speed, innovate at scale, and put humans at the center. You will provide technical guidance and share knowledge with team members with diverse skills and backgrounds. You will consistently deliver quality client services, focusing on more complex, judgmental, and specialized issues surrounding modern AI, foundation models, and emerging technology. You will demonstrate deep technical capabilities and professional knowledge, and you will lead through making.
Strong, hands-on data scientist who codes comfortable building and shipping models, pipelines, services, and experimental frameworks, not just specifying them.
Deep technical breadth across modern AI foundation models and prompting, retrieval and grounding, embeddings and fine-tuning, classical ML, optimization, and experimentation rigor.
Working knowledge of agentic systems and cognitive harness / agent-runtime architectures - memory, tools, policies, evaluation, observability, cost and the trade-offs between them.
Familiarity with at least one major agent SDK (Google ADK, AWS Bedrock AgentCore, LangGraph, AutoGen, OpenAI Agents SDK) and the ability to compare them critically.
Experience designing and operating production AI systems on cloud platforms (GCP, AWS, Azure, Databricks) including responsible-AI guardrails, monitoring, and continuous evaluation.
Track record of leading data-science teams across multiple projects setting technical strategy, mentoring, and raising the bar on rigor and delivery quality.
Excellent communication skills able to explain complex AI concepts to executive clients, and able to defend technical choices in front of architects, engineers, and researchers.
Comfortable moving between problem spaces - equally credible designing a memory architecture, evaluating a forecasting model, or shaping a new agentic workflow.

View full posting on CareerOneStop → ID: cd7c9bd89325

Data Scientist, Manufacturing Analytics

Ford Motor Company · Salem, OR

Mid-level Doctorate

2026-05-21

OR 2026-05-21

Responsibilities

Accelerate the application of value-added analytics and machine learning into the portfolio of products for Manufacturing Analytics.
Drive analytic excellence into product teams by collaborating with Data Scientists, Data Engineers and Software Engineers in analytic and machine learning methods.
Work closely with the Product Manager and Product Owner to translate Business Value needs into analytic deliverables and, where appropriate, software products for delivery by product teams.
Work hands-on with the team and other partners to deliver solutions that meet our customer's requirements and needs.
Act as a consultant to the business vs. an order taker.
Balance "doing it right" with "speed to delivery" by identifying and mitigating risk, generating options, educating business and other decision makers, and taking on justified technical debt.
*You'll have...
Bachelor's degree in a quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics OR Computer Science
2+ year experience hands-on experience with mathematical programming, machine learning, artificial intelligence, optimization/simulation techniques, or statistical analysis
1+ year of experience delivering analytics solutions
1+ year experience with Agile team methodology
Demonstrated technical skills in data analytics, AI/ML, operations research, and/or optimization
*Even better, you may have...
Master's degree or PhD preferred in quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics, Computer Science, or related field
Knowledge and experience working with OGC and related teams/activities (e.g., Compliance, Litigation and Regulatory)
Proven experience with developing data products/solutions to support analytic applications in Ford's data ecosystem
Experience with Product Driven Operating Model or Agile Product Development Process
Proven proficiency in developing and deploying analytic models, working in a team environment, supporting customers and/or end users
Comfortable working in an environment where problems are not always well-defined
Strong interpersonal and leadership skills, with ability to communicate complex topics to leaders and peers in a simple and clear manne
Well-organized, independent, and ready to work with minimal supervision
Inquisitive, proactive, and interested in learning new tools and techniques
Demonstrated hands on experience with deploying data products and/or analytic models in Ford's on-prem and/or Google Cloud Platform
Demonstrated experience to translate real-world business problems into analytical formulations and interpreting analytics results with non-analytics business partners
Working knowledge of Manufacturing IT legacy systems such as FIS, Maximo, QLS, etc.
Thorough understanding of the 'Common Data Model' standard published by Manufacturing
Understanding of the IIoT Platform architecture including MQTT
You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder...or all of the above? No matter what you choose, we offer a work life that works for you, including:
Immediate medical, dental, vision and prescription drug coverage
Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
Vehicle discount program for employees and family members and management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service
A generous schedule of paid holidays, including the week between Christmas and New Year's Day
Paid time off and the option to purchase additional vacation time.
This position is a salary grade 5 - salary grade 8 and ranges from $68,300-$192,900.

View full posting on CareerOneStop → ID: bfc28dd922c9

Senior Data Scientist - Fleet Analytics

The Hertz Corporation · Salem, OR

Senior Master's

2026-05-21

OR 2026-05-21

Requirements

3-5 years hands-on experience in a data scientist role
3+ years of data querying languages (e.g. SQL) and scripting languages (e.g. Python)
3+ years of end-to-end machine learning model development experience (e.g. problem statement definition, exploratory data analysis, feature engineering, model development / tuning, and deployment)
Demonstrated experience using machine learning to drive a business impact
Experience in a ML or data scientist role with car rental or technology company.
Bachelor or Masters degree in Computer Science, or other quantitative discipline such as statistics, mathematics, physics or engineering
*What You'll Get:
Up to 40% off any standard Hertz Rental??
Medical, Dental & Vision plan options
Retirement programs, including 401(k) employer matching
Paid Parental Leave & Adoption Assistance
Employee Assistance Program for employees & family
Educational Reimbursement & Discounts
Voluntary Insurance Programs - Pet, Legal/Identity Theft, Critical Illness
Perks & Discounts -Theme Park Tickets, Gym Discounts & more
The Hertz Corporation operates the Hertz, Dollar Car Rental, Thrifty Car Rental brands in approximately 9,700 corporate and franchisee locations throughout North America, Europe, The Caribbean, Latin America, Africa, the Middle East, Asia, Australia and New Zealand. The Hertz Corporation is one of the largest worldwide airport general use vehicle rental companies, and the Hertz brand is one of the most recognized in the world.

Responsibilities

At Hertz, we are at the forefront of innovation, leveraging cutting-edge technologies to build the best damage management technologies in the transportation industry. We want the brightest AI & ML minds to join our Damage Science Team to help us develop and/or maintain capabilities. Examples of projects the team work on include the below:L
Rationalize Repair Estimates and Invoices with Large Language Models (LLMs): Implement sophisticated LLMs to make intelligent repair routing decisions, ensuring repairs are conducted efficiently and cost-effectively.
Forecast Repair Needs: Develop models to predict future repair & maintenance needs based on historical data and trends.
Optimize Decision Making: Create models to determine if we should keep/sell/salvage a vehicle.
Demand Planning: Forecast customer demand at a given location at a given time.
*What You Will Do:
Formulate the strategic and tactical steps to carry out the model development lifecycle end-to-end (i.e. problem statement definition, exploratory data analysis, feature engineering, model development / tuning, and model implementation).
Build and maintain descriptive, predictive, and prescriptive models to measure the performance of the new products and services
Define and implement best practices to generate accurate analytics, reports, visualizations, and dashboards to explain results simply and succinctly to technical, non-technical, and senior management
Build partnerships and work cross-functionally to identify use cases and opportunities to enhance operational efficiency and drive business value through positive impact on OKRs.
Work with an owner mentality to drive business impact even if that means supporting pipeline creation or decision support analytics.

View full posting on CareerOneStop → ID: 19e6bdef9dfe

Data Scientist, Manufacturing Analytics

Ford Motor Company · Helena, MT

Mid-level

2026-05-21

MT 2026-05-21

View full posting on CareerOneStop → ID: 6a533828e269

Senior Data Scientist - Fleet Analytics

The Hertz Corporation · Helena, MT

Senior

2026-05-21

MT 2026-05-21

View full posting on CareerOneStop → ID: 89b4c308be18

Lead/Principal Data Scientist - Multiple Positions

Boston Consulting Group, Inc. · Seattle, WA

Senior

2026-05-21

WA 2026-05-21

View full posting on CareerOneStop → ID: 107fc508db55

Machine Learning Engineer, Foundation Model Services

Apple · Seattle, WA

Mid-level

2026-05-21

WA 2026-05-21

View full posting on CareerOneStop → ID: 94d3655636d4

Senior Manager, Data Science and Analytics, Prime Video Personalization & Analytics

Amazon · Seattle, WA

Manager

2026-05-21

WA 2026-05-21

View full posting on CareerOneStop → ID: 5f7a59868129

Senior SDE, Machine Learning, Prime Video Personalization & Discovery

Amazon · Seattle, WA

Senior

2026-05-21

WA 2026-05-21

View full posting on CareerOneStop → ID: 982fb1cd6aa7

Data Scientist , AMXL Worldwide Science

Amazon · Bellevue, WA

Mid-level Doctorate

2026-05-20

WA 2026-05-20

Requirements

Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of guiding and coaching a group of researchers experience
1+ years of working with or evaluating AI systems experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Experience applying theoretical models in an applied environment

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

Apply machine learning, statistical modeling, time series analysis, and operations research techniques to build solutions for delivery routing, capacity planning, demand forecasting, workforce scheduling, and network optimization
Analyze large-scale historical and real-time operational data to surface efficiency patterns, bottlenecks, and emerging trends across the AMXL network
Develop, validate, and deploy models that improve cost-to-serve and customer experience
Partner with cross-functional teams to implement data-driven strategies and measure impact
Build scalable, automated pipelines for data ingestion, feature engineering, model training, and validation
Monitor deployed model performance and communicate results through clear reporting on key operational and business metrics

View full posting on CareerOneStop → ID: 22260e66a090

Finance Manager, Advertising Finance - Measurement, Ad Tech, and Data Science (MADS)

Amazon · Seattle, WA

Manager Master's

2026-05-20

WA 2026-05-20

Requirements

Bachelor's degree in Finance, Accounting, Business, Economics or a highly analytical field (e.g., Engineering, Math, and Computer Science)
5+ years of finance or a related analytical field experience
Experience coordinating between technical teams, peers and business stakeholders
5+ years of experience creating financial models and strategic analyses that support business decisions

Preferred

Experience in TM1, Data Warehouse and SQL
Experience with AI/ML technologies
Experience leading financial technology automation and process improvement initiatives with tech and non-tech teams
Advertising or Media experience is a plus

Responsibilities

Business Partnering & Performance Management
Serve as the finance partner for Performance Measurement and Infrastructure leadership
Advise engineering and product leaders on risks, opportunities, and trade-offs impacting quarterly and annual goals
Run weekly business reviews, define and report KPIs, and communicate financials to senior MADS leadership
Support monthly business reviews with insights, variance analysis, and recommendations
Strategic Analysis & Cost Management
Manage hardware cost analysis for Infrastructure, partnering with engineering on capacity planning and cost efficiency
Provide financial modeling and strategic analysis for PRFAQs, product roadmap decisions, and investment trade-offs
Deliver analyses that translate complex technical problems into actionable insights for senior leadership
Partner with BIE and analytics teams to build scalable dashboards and automated reporting
Cross-Functional Collaboration & Operational Excellence
Partner with product, engineering, data science, and sales teams to align strategy with business priorities
Collaborate across Advertising Finance to ensure consistency in planning and reporting
Leverage AI tools daily to raise the speed and quality of finance work, and build AI-powered solutions for the team
Drive process improvements that simplify and scale finance mechanisms, insisting on the highest standards in data accuracy and rigo

View full posting on CareerOneStop → ID: 0c166170a6d9

Principal Product Manager, Data Science

Norstella · Olympia, WA

Manager Master's

2026-05-20

WA 2026-05-20

Requirements

6+ years of experience applying AI / ML to business applications and delivering data driven solutions.
Proven track record of innovating on behalf of the customer in close collaboration with business teams and delivering revenue generating products into production.
Graduate degree in Computer Science, Engineering, Statistics or a related quantitative discipline, or equivalent work experience.
Substantial depth and breadth in NLP, Deep Learning, Generative AI and other state of the art AI / ML techniques.
Excellent knowledge of high-level programming languages (Python, Java, or C++) and core data science libraries including Pandas, NumPy and other similar libraries.
Experience with delivering large-scale distributed systems in an agile environment and the ability to build quick prototypes.
Experience leading a portfolio of complex data science projects and mentoring junior team members.
Excellent problem solving and communication skills.

Preferred

Knowledge of the healthcare domain and experience with applying AI to healthcare data.
Experience with AWS especially in relation to ML workflows with SageMaker, serverless compute and storage such as S3 and Snowflake.
Experience with LLMs, prompt engineering, retrieval augmented generation, model fine tuning and knowledge graphs.

Responsibilities

In this role as a Principal Product Manager, Data Science, you will:
Collaborate with product leadership to identity, elaborate and prioritize projects.
Partner with business-product managers to explore new opportunities to build customer facing capabilities with AI and build and maintain the data science project pipeline.
Help define requirements and success metrics for identified projects and collaborate with data scientists and engineers to deliver on the commitments.
Lead marketing activities for the data science team, facilitate ideation sessions to help the entire product organization innovate, and introduce processes that promote transparent prioritization, data-driven decision making, and reuse of our platforms and capabilities across the company.
Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal teams on these developments.
Serve as the company-wide expert in one or more complex technical areas and its business applications (e.g., entity mastering, knowledge graphs, search optimization, RAG).
All other duties, as assigned.

View full posting on CareerOneStop → ID: 352068afaa9f

Senior Applied Data Scientist

Eliassen Group · Olympia, WA

Senior Doctorate

2026-05-20

WA 2026-05-20

Requirements

Strong applied data science background, including optimization, forecasting, or prescriptive analytics in a business environment
Proficient Python development skills with experience supporting or deploying models in production systems
Strong SQL expertise, including complex query writing and performance tuning

Education

PhD in a quantitative field (e.g., Data Science, Mathematics, Statistics, Computer Science, Industrial Engineering, Operations Research) with 2+ years of applied industry experience OR
Master's degree in a quantitative field with 5+ years of applied data science experience OR
Bachelor's degree in a quantitative or technical field with 7+ years of applied data science experience
*_Recruitment Transparency Notice_
*_Eliassen Group values transparency in our recruitment practices. Please be advised that Eliassen Group utilizes artificial intelligence (AI) tools as part of its initial application screening_ _and hiring_ _process. You may receive email and SMS notifications from the Eliassen Virtual Recruiting Team (_ _noreply@eliassen.com_ _, 781-808-2924) inviting you to complete a brief voice screening as part of your application process. These tools assist our hiring teams in different ways, including but not limited to, assistance in reviewing application materials to help identify candidates whose qualifications most closely match the requirements of the position. All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring decisions are made. The use of AI in our process is intended to support fairness, efficiency, and consistency, and Eliassen Group takes measures to prevent bias or discrimination in connection with its hiring practices. By proceeding, you acknowledge, agree, and consent to Eliassen Group's use of these tools, including AI tools, as part of the application and hiring process._
_Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range._

Responsibilities

Design, develop, and own applied data science and optimization models supporting a pricing engine for products and services
Apply prescriptive analytics, forecasting, and operations research techniques to pricing, discounting, and value optimization problems
Translate business requirements into mathematical formulations and data-driven solutions with measurable business impact
Operationalize and support models using production-quality Python development to deploy solutions into production environments
Write, optimize, and tune complex SQL queries to support large-scale data access, feature generation, and model validation

View full posting on CareerOneStop → ID: 033f9d0d7814

Data Scientist II

Chewy Inc. · Bellevue, WA

Mid-level Master's

2026-05-20

WA 2026-05-20

Requirements

Ability to work with large datasets using distributed computing tools;
Amazon Web Services tools such as Redshift, Snowflake, Google Big Query, SageMaker or other similar platforms;
Object-oriented programming with Python; and
Data visualization tools and packages (Tableau or similar).

View full posting on CareerOneStop → ID: 0ef76487d159

Data Scientist III

Chewy Inc. · Bellevue, WA

Mid-level Doctorate

2026-05-20

WA 2026-05-20

Requirements

At least one data science subject area (e.g., casual inference, LLM's, forecasting, etc.);
Managing the entire data science lifecycle including data prep, exploratory data analysis, modeling, interface with cross functional stakeholders (such as engineering, business, etc.), deploying models to production;
Amazon Web Services tools such as Snowflake;
R, PySpark, Spark, Keras, TensorFlow, Docker, Git version control;
Object-oriented programming with Python;
Data visualization tools and packages (Tableau or similar); and

View full posting on CareerOneStop → ID: 8464227eb95e

Data Scientist III

Chewy Inc. · Bellevue, WA

Mid-level Doctorate

2026-05-20

WA 2026-05-20

Requirements

At least one data science subject area (e.g., casual inference, NLP, forecasting, etc.);
R, PySpark, Spark, Scala, Java, PyTorch, TensorFlow, Docker;
Object-oriented programming with Python; and
Data visualization tools and packages (Tableau or similar).
Managing the entire data science lifecycle including data prep, exploratory data analysis, modeling, interface with engineering;
Amazon Web Services tools such as Redshift, Snowflake, SageMaker or other similar platforms; and

View full posting on CareerOneStop → ID: a50291e8d3d9

Machine Learning Platform Engineer, Apple Services Engineering

Apple · Seattle, WA

Mid-level

2026-05-20

WA 2026-05-20

Requirements

4-8 years of software engineering experience building and shipping production services.
Strong Python. You're fluent with FastAPI, Pydantic, and the modern Python ecosystem. You write code that's clean, tested, and easy for the next person to pick up.
Builder's mindset. You enjoy shipping. You're comfortable iterating quickly on scoped problems and knowing when to slow down for the parts that need it.
Fluency with AI coding tools. You actively use tools like Claude Code (or equivalents) in your day-to-day workflow, including features like skills, slash commands, and agent-style workflows. You have a good intuition for when to lean on them, when to steer them, and how to get high-quality output.
Familiarity with the agentic LLM landscape. You stay current on how modern LLM systems work in production - tool use, MCP servers, agent frameworks, context management, multi-step reasoning. You can hold a real conversation about the tradeoffs.
Hands-on evaluation experience. You've built evaluations for your own agents or LLM systems, or you've worked with evaluation orchestration frameworks like Inspect, Braintrust, LangSmith, Promptfoo, or equivalents (including internal tooling). You understand what makes an evaluation trustworthy vs. theatrical.
Real working knowledge of LLMs in production. You're comfortable with prompt iteration, dataset curation, judge models, and statistical reasoning about non-deterministic outputs. You understand the lifecycle around models even if you haven't trained them yourself.
Solid engineering fundamentals. You understand testing, CI/CD, containerization (Docker), and basic observability. You've shipped services that others depend on and stayed close when they broke.
Clear communicator. You write clear PRs, ask sharp questions, and flag blockers early. You're comfortable disagreeing thoughtfully and changing your mind when the argument is good.
Ownership. When something is broken or unclear, you tend to pick it up rather than wait. You either move it forward or surface it clearly.

Preferred

Experience working on developer platforms, internal tools, or SDKs
Production experience with LLM/agent systems - building, evaluating, or operating them
Familiarity with job orchestration frameworks (Temporal.io, Airflow, or similar)
Distributed compute experience (Ray, Dask, or Kubernetes-based job systems)
Experience with experiment tracking or ML lifecycle tooling (Weights & Biases, MLflow, etc.)
Startup or early-stage experience where you wore multiple hats and shipped under constraint

Responsibilities

We're building the evaluation platform that will serve all of Apple's generative AI and agent systems. Evaluating non-deterministic AI systems is one of the hardest unsolved problems in production ML - and one Apple has to get right at scale. We're building the platform that makes it tractable for every team here.
This is a hands-on engineering role with a lot of autonomy. You'll write a lot of Python and own meaningful pieces of the platform end-to-end. You'll be partnering closely with research engineers, model and serving teams, product and feature teams, and the infra and data platform groups this work integrates with.
Build and ship: Take ownership of features and services within the evaluation platform: APIs, SDKs, orchestration components, evaluation runners. You'll have the room to make calls on your own work and the support to deliver it well.
Productionize ML research: Partner with research engineers to take their prototype code and turn it into reliable services. You'll learn their world quickly and translate research patterns into clean Python that holds up under real load.
Move fast, responsibly: You'll get scoped problems with room to figure out the how. We trust you to balance speed with care, to know when something needs a quick prototype and when it needs a design doc, tests, and a careful rollout.
Improve as you go: Notice the rough edges and pick them up. The flaky test, the slow build, the confusing API, the runbook that's out of date. We want someone who leaves the codebase a little better every week.
Developer experience: Help build the SDKs and abstractions that other Apple teams use to evaluate their models and agents. You'll feel the friction of bad ergonomics directly, which puts you in a great position to fix it.
Operational ownership: Your code runs in production. You write the tests, set up the CI, add the metrics, and stay close when something breaks. You don't need to be an SRE, but you take care of what you ship.

View full posting on CareerOneStop → ID: 152821a80d55

Senior Software Development Engineer - AI / Data Science

IBM · Seattle, WA

Senior

2026-05-20

WA 2026-05-20

Requirements

Partner with engineering teams across the organization to understand their AI delivery needs and translate them into platform capabilities, SDKs, and reusable components.
Develop and maintain self-service tooling, APIs, and documentation that enable product engineers to integrate AI capabilities without deep platform expertise.
Establish and enforce platform engineering standards around security, observability, cost management, and AI governance to ensure responsible AI delivery at scale.
Data & AI Intelligence
Build and maintain AI-driven pipelines that process complex customer data to identify, surface, and deliver actionable business value through intelligent automation and insight generation.
Collaborate with data scientists to productionize models and analytical workflows, ensuring seamless integration with platform data infrastructure including data lakes, warehouses, and streaming systems.
Instrument platform telemetry and evaluation frameworks to measure AI system quality, latency, cost, and business impact across consuming teams.
Technical Leadership & Collaboration
Serve as a technical leader and trusted partner across principal engineers, staff engineers, and data science disciplines - driving alignment on platform architecture and engineering standards.
Participate in design reviews, threat modeling, and architectural decision-making, advocating for scalable, maintainable, and secure platform patterns.
Mentor mid-level engineers through code reviews, pairing sessions, and technical guidance, raising the engineering bar across the broader platform team.
*Required technical and professional expertise
5+ years of professional software development experience, with demonstrated depth in backend platform or infrastructure engineering with proven experience designing and building distributed systems or platform-level services that serve multiple internal engineering teams.
Hands-on experience with large language model (LLM) integration, including prompt engineering, model API consumption, and managing inference pipelines in production.
Strong proficiency in Python and/or Java/Go, with demonstrated ability to engineer production-quality, maintainable, and well-tested code with a solid understanding of RESTful API design, event-driven architecture, and asynchronous processing patterns as they apply to AI platform services.
Experience with major cloud platforms (AWS preferred) and the services relevant to AI/ML workloads - including managed compute, storage, and model serving infrastructure.
Experience working with AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent agentic tooling.

Preferred

Experience with MCP (Model Context Protocol) or A2A (Agent-to-Agent) protocol design and implementation within multi-agent AI systems.
Hands-on experience with AWS Bedrock, Azure AI Foundry, or watsonx as a managed AI platform for model hosting, fine-tuning, or inference routing.
Familiarity with LiteLLM, OpenRouter, or similar LLM proxy/routing layers for abstracting multi-model inference across providers.
Experience with Snowflake, including Snowpark, Cortex AI features, or Time Travel, as part of a data platform or AI analytics workflow.
Background in IBM enterprise platforms including Apptio, Cloudability, or IBM ContextForge, with awareness of how AI augments financial and cloud cost management use cases.
Knowledge of AI governance, responsible AI practices, and security controls for AI systems - including data privacy, access control, and output guardrails.
Experience with observability tooling applied to AI systems - including LLM evaluation frameworks, token cost tracking, latency profiling, and quality metrics pipelines.
Exposure to AI compliance requirements (e.g., FIPS, SOC 2, FedRAMP) and how they shape platform architecture decisions in regulated enterprise environments.
Contributions to open-source AI tooling, published technical writing, or demonstrated thought leadership in the generative AI or ML platform space.
Experience building internal developer platforms (IDPs) or platform-as-product models where the primary customer is an internal engineering audience.

Responsibilities

Platform Design & Engineering
Design, build, and maintain a scalable AI Platform that supports multiple engineering teams in delivering natural language conversation, RAG-based retrieval, and AI-driven data solutions.
Develop core platform services including LLM routing, model abstraction layers, prompt management, and inference orchestration across cloud and on-premise infrastructure.
Architect and implement RAG pipelines - including vector store integration, document ingestion, chunking strategies, and retrieval optimization - enabling teams to ground AI responses in enterprise data.
Build secure, governed data access patterns that allow AI agents and models to query complex structured and unstructured data sources safely and efficiently.
AI Agent & Agentic Framework Development
Engineer agentic capabilities including multi-step reasoning, tool use, and agent-to-agent (A2A) coordination patterns that empower downstream teams to deliver autonomous AI workflows.
Implement and maintain MCP (Model Context Protocol) server registrations, enabling standardized tool discovery and invocation across the platform ecosystem.
Contribute to the design of circuit breaking, retry logic, and guardrail mechanisms that ensure safe and reliable agentic behavior in production environments.

View full posting on CareerOneStop → ID: ebb9936d6941

Senior Software Development Engineer - AI / Data Science

IBM · Bellevue, WA

Senior

2026-05-20

WA 2026-05-20

Requirements

Partner with engineering teams across the organization to understand their AI delivery needs and translate them into platform capabilities, SDKs, and reusable components.
Develop and maintain self-service tooling, APIs, and documentation that enable product engineers to integrate AI capabilities without deep platform expertise.
Establish and enforce platform engineering standards around security, observability, cost management, and AI governance to ensure responsible AI delivery at scale.
Data & AI Intelligence
Build and maintain AI-driven pipelines that process complex customer data to identify, surface, and deliver actionable business value through intelligent automation and insight generation.
Collaborate with data scientists to productionize models and analytical workflows, ensuring seamless integration with platform data infrastructure including data lakes, warehouses, and streaming systems.
Instrument platform telemetry and evaluation frameworks to measure AI system quality, latency, cost, and business impact across consuming teams.
Technical Leadership & Collaboration
Serve as a technical leader and trusted partner across principal engineers, staff engineers, and data science disciplines - driving alignment on platform architecture and engineering standards.
Participate in design reviews, threat modeling, and architectural decision-making, advocating for scalable, maintainable, and secure platform patterns.
Mentor mid-level engineers through code reviews, pairing sessions, and technical guidance, raising the engineering bar across the broader platform team.
*Required technical and professional expertise
5+ years of professional software development experience, with demonstrated depth in backend platform or infrastructure engineering with proven experience designing and building distributed systems or platform-level services that serve multiple internal engineering teams.
Hands-on experience with large language model (LLM) integration, including prompt engineering, model API consumption, and managing inference pipelines in production.
Strong proficiency in Python and/or Java/Go, with demonstrated ability to engineer production-quality, maintainable, and well-tested code with a solid understanding of RESTful API design, event-driven architecture, and asynchronous processing patterns as they apply to AI platform services.
Experience with major cloud platforms (AWS preferred) and the services relevant to AI/ML workloads - including managed compute, storage, and model serving infrastructure.
Experience working with AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent agentic tooling.

Preferred

Experience with MCP (Model Context Protocol) or A2A (Agent-to-Agent) protocol design and implementation within multi-agent AI systems.
Hands-on experience with AWS Bedrock, Azure AI Foundry, or watsonx as a managed AI platform for model hosting, fine-tuning, or inference routing.
Familiarity with LiteLLM, OpenRouter, or similar LLM proxy/routing layers for abstracting multi-model inference across providers.
Experience with Snowflake, including Snowpark, Cortex AI features, or Time Travel, as part of a data platform or AI analytics workflow.
Background in IBM enterprise platforms including Apptio, Cloudability, or IBM ContextForge, with awareness of how AI augments financial and cloud cost management use cases.
Knowledge of AI governance, responsible AI practices, and security controls for AI systems - including data privacy, access control, and output guardrails.
Experience with observability tooling applied to AI systems - including LLM evaluation frameworks, token cost tracking, latency profiling, and quality metrics pipelines.
Exposure to AI compliance requirements (e.g., FIPS, SOC 2, FedRAMP) and how they shape platform architecture decisions in regulated enterprise environments.
Contributions to open-source AI tooling, published technical writing, or demonstrated thought leadership in the generative AI or ML platform space.
Experience building internal developer platforms (IDPs) or platform-as-product models where the primary customer is an internal engineering audience.

Responsibilities

Platform Design & Engineering
Design, build, and maintain a scalable AI Platform that supports multiple engineering teams in delivering natural language conversation, RAG-based retrieval, and AI-driven data solutions.
Develop core platform services including LLM routing, model abstraction layers, prompt management, and inference orchestration across cloud and on-premise infrastructure.
Architect and implement RAG pipelines - including vector store integration, document ingestion, chunking strategies, and retrieval optimization - enabling teams to ground AI responses in enterprise data.
Build secure, governed data access patterns that allow AI agents and models to query complex structured and unstructured data sources safely and efficiently.
AI Agent & Agentic Framework Development
Engineer agentic capabilities including multi-step reasoning, tool use, and agent-to-agent (A2A) coordination patterns that empower downstream teams to deliver autonomous AI workflows.
Implement and maintain MCP (Model Context Protocol) server registrations, enabling standardized tool discovery and invocation across the platform ecosystem.
Contribute to the design of circuit breaking, retry logic, and guardrail mechanisms that ensure safe and reliable agentic behavior in production environments.

View full posting on CareerOneStop → ID: ce3ea2b59280

Principal Product Manager, Data Science

Norstella · Boise, ID

Manager Master's

2026-05-20

ID 2026-05-20

Requirements

6+ years of experience applying AI / ML to business applications and delivering data driven solutions.
Proven track record of innovating on behalf of the customer in close collaboration with business teams and delivering revenue generating products into production.
Graduate degree in Computer Science, Engineering, Statistics or a related quantitative discipline, or equivalent work experience.
Substantial depth and breadth in NLP, Deep Learning, Generative AI and other state of the art AI / ML techniques.
Excellent knowledge of high-level programming languages (Python, Java, or C++) and core data science libraries including Pandas, NumPy and other similar libraries.
Experience with delivering large-scale distributed systems in an agile environment and the ability to build quick prototypes.
Experience leading a portfolio of complex data science projects and mentoring junior team members.
Excellent problem solving and communication skills.

Preferred

Knowledge of the healthcare domain and experience with applying AI to healthcare data.
Experience with AWS especially in relation to ML workflows with SageMaker, serverless compute and storage such as S3 and Snowflake.
Experience with LLMs, prompt engineering, retrieval augmented generation, model fine tuning and knowledge graphs.

Responsibilities

In this role as a Principal Product Manager, Data Science, you will:
Collaborate with product leadership to identity, elaborate and prioritize projects.
Partner with business-product managers to explore new opportunities to build customer facing capabilities with AI and build and maintain the data science project pipeline.
Help define requirements and success metrics for identified projects and collaborate with data scientists and engineers to deliver on the commitments.
Lead marketing activities for the data science team, facilitate ideation sessions to help the entire product organization innovate, and introduce processes that promote transparent prioritization, data-driven decision making, and reuse of our platforms and capabilities across the company.
Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal teams on these developments.
Serve as the company-wide expert in one or more complex technical areas and its business applications (e.g., entity mastering, knowledge graphs, search optimization, RAG).
All other duties, as assigned.

View full posting on CareerOneStop → ID: 0925bd9bfd98

Senior Applied Data Scientist

Eliassen Group · Boise, ID

Senior Doctorate

2026-05-20

ID 2026-05-20

Requirements

Strong applied data science background, including optimization, forecasting, or prescriptive analytics in a business environment
Proficient Python development skills with experience supporting or deploying models in production systems
Strong SQL expertise, including complex query writing and performance tuning

Education

PhD in a quantitative field (e.g., Data Science, Mathematics, Statistics, Computer Science, Industrial Engineering, Operations Research) with 2+ years of applied industry experience OR
Master's degree in a quantitative field with 5+ years of applied data science experience OR
Bachelor's degree in a quantitative or technical field with 7+ years of applied data science experience
*_Recruitment Transparency Notice_
*_Eliassen Group values transparency in our recruitment practices. Please be advised that Eliassen Group utilizes artificial intelligence (AI) tools as part of its initial application screening_ _and hiring_ _process. You may receive email and SMS notifications from the Eliassen Virtual Recruiting Team (_ _noreply@eliassen.com_ _, 781-808-2924) inviting you to complete a brief voice screening as part of your application process. These tools assist our hiring teams in different ways, including but not limited to, assistance in reviewing application materials to help identify candidates whose qualifications most closely match the requirements of the position. All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring decisions are made. The use of AI in our process is intended to support fairness, efficiency, and consistency, and Eliassen Group takes measures to prevent bias or discrimination in connection with its hiring practices. By proceeding, you acknowledge, agree, and consent to Eliassen Group's use of these tools, including AI tools, as part of the application and hiring process._
_Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range._

Responsibilities

Design, develop, and own applied data science and optimization models supporting a pricing engine for products and services
Apply prescriptive analytics, forecasting, and operations research techniques to pricing, discounting, and value optimization problems
Translate business requirements into mathematical formulations and data-driven solutions with measurable business impact
Operationalize and support models using production-quality Python development to deploy solutions into production environments
Write, optimize, and tune complex SQL queries to support large-scale data access, feature generation, and model validation

View full posting on CareerOneStop → ID: 3728f1ac05fe

Lead Data Scientist - Forecasting

CVS Health · Salem, OR

Senior Doctorate

2026-05-20

OR 2026-05-20

Requirements

Master'sdegree in Statistics, Mathematics, Computer Science, Engineering, Economics, or relatedquantitative field(PhD preferred)
7+ years of experience in forecasting or demand modeling,ideally in a retail or B2C environmentincludinghands-ondeploying enterprise-levelproduction forecasting systems with measurable impact
3+ years of experienceworking with a data engineering/MLOpsteam toproductionizedata science models, familiarity with version control (GitLab or GitHub), and ML platforms (AWS SageMaker, Databricks, GCP Vertex AI, etc.)
4+ years of experience with Python and SQL for large-scale data processing
Excellent communication, leadership, and presentation skills and attention to detail. Worked in an agile environment, has the flexibility to adapt to changing business needs
Proven experience leading multiple complex projects simultaneously in a fast-paced environment.
Experience mentoring junior team members and setting standards for forecasting approaches, model validation, and code quality

Preferred

Experience applyingdemandforecastingmethodsin a retail environment
In depthunderstandingof merchandising concepts and metrics
Experience managing large scale projects and working with multiple stakeholders in a matrixed environment

Education

Master's degree in Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative field
Advanced degree (PhD) preferred in quantitative disciplines with applied experience in forecasting,

Responsibilities

The Forecasting Center of Excellence (COE) at CVS Health builds scalable forecasting systems that support pricing, promotions, and assortment decisions across the retail business. As a Lead Data Scientist, you will own how demand is modeled and used for decision-making, not just how it is predicted.
This role focuses on defining and scaling a unified forecasting framework that produces consistent outputs across use cases. You will work with data science, engineering, product management, software development, and business teams to ensure forecasts are not just accurate, but stable, and usable in real decision workflows.
*In this role, you will have the opportunity to:
Own thedesign andevolutionof a unified forecastingarchitecture, defininghow demand is constructed
Integrate internal and external data sources (e.g., coupon redemption, merchandising, competitive, macroeconomic) into scalable forecasting pipelines
Evaluate tradeoffs across various forecasting methods (and ensure outputs are stable, interpretable, and decision-ready
Develop scenario planning and simulation frameworks to measure the business impact of pricing, promotions, and assortment decisions
Implement robustMLOpspractices for deployment, monitoring, and retraining in cloud environments (Azure, GCP, AWS)
Elevate the technical bar of the entire organization. Establish a culture ofcontinouslearning and champion the recruitment oftop-tier analyticaltalent
Lead the exploration ofstate-of-the-artmachine learning/deep learningtechniques.
Translate complex businessobjectivesinto a multi-quarter data science roadmap, prioritizing high impact initiatives from research through deployment while managing technical debt and ensuring alignment with cross-functional product milestones.
We are a fast-paced team focused on building innovative advanced analytics solutions using cloud capabilities. Within our team, we believe cutting-edge AI products and analytics can only be delivered if every aspect of the solution from data to model to front end UI is fully designed and developed by the team.
We are looking for talented individuals who have a strong sense of ownership, accountability and a desire to deliver high quality end to end intuitive and impactful analytic products using advanced data driven approaches.

View full posting on CareerOneStop → ID: 9e79fde8e216

Principal Product Manager, Data Science

Norstella · Salem, OR

Manager Master's

2026-05-20

OR 2026-05-20

Requirements

6+ years of experience applying AI / ML to business applications and delivering data driven solutions.
Proven track record of innovating on behalf of the customer in close collaboration with business teams and delivering revenue generating products into production.
Graduate degree in Computer Science, Engineering, Statistics or a related quantitative discipline, or equivalent work experience.
Substantial depth and breadth in NLP, Deep Learning, Generative AI and other state of the art AI / ML techniques.
Excellent knowledge of high-level programming languages (Python, Java, or C++) and core data science libraries including Pandas, NumPy and other similar libraries.
Experience with delivering large-scale distributed systems in an agile environment and the ability to build quick prototypes.
Experience leading a portfolio of complex data science projects and mentoring junior team members.
Excellent problem solving and communication skills.

Preferred

Knowledge of the healthcare domain and experience with applying AI to healthcare data.
Experience with AWS especially in relation to ML workflows with SageMaker, serverless compute and storage such as S3 and Snowflake.
Experience with LLMs, prompt engineering, retrieval augmented generation, model fine tuning and knowledge graphs.

Responsibilities

In this role as a Principal Product Manager, Data Science, you will:
Collaborate with product leadership to identity, elaborate and prioritize projects.
Partner with business-product managers to explore new opportunities to build customer facing capabilities with AI and build and maintain the data science project pipeline.
Help define requirements and success metrics for identified projects and collaborate with data scientists and engineers to deliver on the commitments.
Lead marketing activities for the data science team, facilitate ideation sessions to help the entire product organization innovate, and introduce processes that promote transparent prioritization, data-driven decision making, and reuse of our platforms and capabilities across the company.
Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal teams on these developments.
Serve as the company-wide expert in one or more complex technical areas and its business applications (e.g., entity mastering, knowledge graphs, search optimization, RAG).
All other duties, as assigned.

View full posting on CareerOneStop → ID: 04cc7306bca0

Senior Applied Data Scientist

Eliassen Group · Salem, OR

Senior Doctorate

2026-05-20

OR 2026-05-20

Requirements

Strong applied data science background, including optimization, forecasting, or prescriptive analytics in a business environment
Proficient Python development skills with experience supporting or deploying models in production systems
Strong SQL expertise, including complex query writing and performance tuning

Education

PhD in a quantitative field (e.g., Data Science, Mathematics, Statistics, Computer Science, Industrial Engineering, Operations Research) with 2+ years of applied industry experience OR
Master's degree in a quantitative field with 5+ years of applied data science experience OR
Bachelor's degree in a quantitative or technical field with 7+ years of applied data science experience
*_Recruitment Transparency Notice_
*_Eliassen Group values transparency in our recruitment practices. Please be advised that Eliassen Group utilizes artificial intelligence (AI) tools as part of its initial application screening_ _and hiring_ _process. You may receive email and SMS notifications from the Eliassen Virtual Recruiting Team (_ _noreply@eliassen.com_ _, 781-808-2924) inviting you to complete a brief voice screening as part of your application process. These tools assist our hiring teams in different ways, including but not limited to, assistance in reviewing application materials to help identify candidates whose qualifications most closely match the requirements of the position. All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring decisions are made. The use of AI in our process is intended to support fairness, efficiency, and consistency, and Eliassen Group takes measures to prevent bias or discrimination in connection with its hiring practices. By proceeding, you acknowledge, agree, and consent to Eliassen Group's use of these tools, including AI tools, as part of the application and hiring process._
_Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range._

Responsibilities

Design, develop, and own applied data science and optimization models supporting a pricing engine for products and services
Apply prescriptive analytics, forecasting, and operations research techniques to pricing, discounting, and value optimization problems
Translate business requirements into mathematical formulations and data-driven solutions with measurable business impact
Operationalize and support models using production-quality Python development to deploy solutions into production environments
Write, optimize, and tune complex SQL queries to support large-scale data access, feature generation, and model validation

View full posting on CareerOneStop → ID: 361d39050991

Principal Product Manager, Data Science

Norstella · Helena, MT

Manager

2026-05-20

MT 2026-05-20

View full posting on CareerOneStop → ID: 4db43b0a5f50

Senior Applied Data Scientist

Eliassen Group · Helena, MT

Senior

2026-05-20

MT 2026-05-20

View full posting on CareerOneStop → ID: cb65e1e89c3e

Data Scientist

Capgemini · Seattle, WA

Mid-level

2026-05-19

WA 2026-05-19

Requirements

Design, develop, and deploy AI enabled applications aligned to enterprise needs.
Translate business problems into scalable technical solutions.
Build Generative AI solutions using large language models, including RAG and tool enabled workflows.
Apply AI assisted code generation and developer productivity tools for tasks such as code scaffolding, refactoring, documentation, and test generation.
Design and integrate application components using REST APIs, authentication, error handling, and observability best practices.
Deploy and operate AI solutions in production or production adjacent environments, supporting monitoring and reliability.
The base compensation range for this role in the posted location is $70,000 - $110,000
Contract Type: Permanent
Seattle, WA, US
Brand: Capgemini
Professional Community: Data & AI

Responsibilities

Capgemini is building a Seattle-based AI Cohort to support strategic enterprise engagements focused on Generative AI, intelligent applications, and advanced analytics. This role combines hands-on AI engineering with a delivery and consulting oriented mindset. You will work closely with business and technical stakeholders to shape, build, and scale AI solutions from early exploration through production delivery. Some engagements may follow a Forward Deployment Engineer (FDE)-style working model, where engineers collaborate closely with client teams during solution design and rollout. However, the role remains broad and well suited for candidates who enjoy combining strong technical problem solving with collaborative, client facing delivery. Many initiatives are centered on enterprise cloud and AI platforms, with a strong preference for Azure based architectures and services, as well as modern developer environments that incorporate AI assisted development and code generation tools.

View full posting on CareerOneStop → ID: 9d0a3ff7ef41

Data Scientist

Capgemini · Seattle, WA

Mid-level

2026-05-19

WA 2026-05-19

Requirements

Design, develop, and deploy AI enabled applications aligned to enterprise needs.
Translate business problems into scalable technical solutions.
Build Generative AI solutions using large language models, including RAG and tool enabled workflows.
Apply AI assisted code generation and developer productivity tools for tasks such as code scaffolding, refactoring, documentation, and test generation.
Design and integrate application components using REST APIs, authentication, error handling, and observability best practices.
Deploy and operate AI solutions in production or production adjacent environments, supporting monitoring and reliability.
The base compensation range for this role in the posted location is $70,000 - $110,000
Contract Type: Permanent
Seattle, WA, US
Brand: Capgemini
Professional Community: Data & AI

Responsibilities

Capgemini is building a Seattle-based AI Cohort to support strategic enterprise engagements focused on Generative AI, intelligent applications, and advanced analytics. This role combines hands-on AI engineering with a delivery and consulting oriented mindset. You will work closely with business and technical stakeholders to shape, build, and scale AI solutions from early exploration through production delivery. Some engagements may follow a Forward Deployment Engineer (FDE)-style working model, where engineers collaborate closely with client teams during solution design and rollout. However, the role remains broad and well suited for candidates who enjoy combining strong technical problem solving with collaborative, client facing delivery. Many initiatives are centered on enterprise cloud and AI platforms, with a strong preference for Azure based architectures and services, as well as modern developer environments that incorporate AI assisted development and code generation tools.

View full posting on CareerOneStop → ID: c1e67c313d4d

Machine Learning Engineer, Apple Services Engineering

Apple · Seattle, WA

Mid-level Master's

2026-05-19

WA 2026-05-19

Requirements

Bachelor's degree in Computer Science, Software Engineering, Mathematics, or a related technical field.
7+ years of relevant work experience.
Strong software engineering fundamentals and technical competence in production-quality software development.
Real-world experience with building, scaling, and deploying recommendation systems or large-scale ML models.
Proven grasp of the open-source Python AI/ML tech stack, including PyTorch, scikit-learn, and numpy-scipy-pandas.
Solid understanding of machine learning algorithms, design patterns, and tools, including deep learning and generative AI.
Proficiency with big data technologies, data processing pipelines, and distributed computing (e.g., Spark, Hadoop, Kafka).
Experience with ML infrastructure, model optimization, and serving models at scale with low latency.
Strong written & oral communication skills, with a collaborative mindset.

Preferred

Master's degree in Computer Science, Software Engineering, Mathematics, or a related field; OR equivalent practical industry experience.
Industry experience specifically focused on MLOps, recommendation systems, or search ranking infrastructure.

Responsibilities

Wonder how Apple's Media Products show relevant search results and recommendations across Apple's media offerings - including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books? Come join us! Design, build, and deploy machine learning pipelines that personalize the App Store for billions of users worldwide! Prototype, scale, and optimize algorithm improvements. Build robust, large-scale personalized recommender systems for Apps, Games, Videos, Podcasts and Fitness. See your work touch the lives of billions of Apple users worldwide.
The Apple Services Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Fitness+. And we do it on a massive scale, meeting Apple's high expectations with high performance, to deliver a huge variety of entertainment in over 35 languages to more than 150 countries.
Our scientists and engineers build secure, end-to-end solutions powered by machine learning. Thanks to Apple's unique integration of hardware, software, and services, designers, scientists and engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, flexible, and multi-functional, offering greater exposure to the array of opportunities here.
We are looking for an exceptional Machine Learning Engineer to help us build and scale personalization systems using the latest advances in machine learning. With your engineering expertise, we want to develop robust, high-performance solutions to power personalized experiences across the App Store that enrich the lives of our customers. You will have the incredible opportunity to partner with researchers to see cutting-edge AI models deployed reliably at Apple's truly incredible global scale.

View full posting on CareerOneStop → ID: 10a0a4edb19a

Senior Machine Learning Engineer - Earner Incentive

Uber · Seattle, WA

Senior Doctorate

2026-05-19

WA 2026-05-19

Requirements

Ph.D., M.S., or Bachelor's degree in Computer Science, Statistics, Mathematics, Machine Learning, Operations Research, or a related field, or equivalent practical experience with demonstrated impact.
5+ years of experience across the end-to-end ML lifecycle, including data analysis, feature engineering, model development, deployment, monitoring, and iteration in large-scale production systems. Proven ability to deliver measurable business impact and strong understanding of MLOps best practices.
Strong understanding of a broad range of ML and statistical techniques, including deep learning (e.g., multi-task learning, transformers), tree-based models, and classical approaches, with solid judgment in selecting methods based on context and data.
Proficiency in at least one production language (Python, Scala, Java, or Go) and common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
Solid software engineering skills, including system design, writing and reviewing production-quality code, testing, and operating ML systems in production.
Strong ownership, learning mindset, collaboration and communication skills; able to work independently and effectively in cross-functional teams.

Preferred

Experience developing and deploying pricing, matching, or incentive algorithms for two-sided marketplaces, with strong product intuition and system-level thinking.
Experience with multi-armed bandits, reinforcement learning, and causal ML, including applying these methods in production systems.
Familiarity with large-scale data and ML infrastructure (e.g. Spark, Flink), and batch or real-time data processing systems.
Strong communication and leadership skills, with the ability to lead initiatives, prototype quickly, drive alignment, and collaborate effectively with cross-functional partners, from early idea generation through productionization.
Experience leading complex technical projects, influencing scope, technical direction, and execution across multiple engineers or teams.
Ability to translate ambiguous business problems into clear, actionable problem statements, define success metrics, and drive execution through well-reasoned trade-offs.
Demonstrated technical leadership, such as mentoring engineers, leading cross-functional efforts, or shaping ML / optimization strategy.
Experience designing, running and analyzing large-scale online experiments to prove impact, interpret results, guide decision-making, and translate insights into concrete product or system changes.
For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Responsibilities

Uber's Marketplace is at the core of the business. The Earner Incentive team in Marketplace builds products and systems that empower drivers through targeted incentives, creating a more balanced and efficient marketplace while enhancing engagement and experience.
The team owns the end-to-end incentive lifecycle, from ML-driven incentive generation to scalable online serving, answering questions such as who, where, when, how, and how much, powered by large-scale machine learning, optimization, and experimentation systems . These systems enable proactive, targeted incentives that shape supply, optimize earnings, and guide marketplace balance.
We are seeking a Senior Machine Learning Engineer to design and scale the technical foundations behind Uber's driver incentive systems. You will develop and productionize large-scale ML models and decision systems that power both scheduled and near real-time, intelligent incentive generation and delivery at Uber's global scale.
In this role, you will collaborate closely with engineers, product managers, operations, and scientists to set technical direction, make thoughtful trade-offs, and turn complex problems into reliable production systems. Your work will directly shape how incentives are designed and delivered at scale, enhancing marketplace efficiency and reliability, and empowering earning opportunities for millions of drivers worldwide.
*What the Candidate Will Do
Design, develop, productionize, and operate end-to-end ML solutions and data pipelines for large-scale systems that power driver incentives.
Develop and apply advanced ML and optimization techniques to design incentive mechanisms for online marketplaces, improving marketplace efficiency and reliability while enabling earning opportunities for millions of drivers.
Build deep domain expertise in incentives, pricing, and marketplace dynamics, and understand how these systems interact with Operations. Translate business requirements into clear problem statements and actionable technical plans, reasoning through trade-offs to deliver practical, production-ready solutions.
Help set the team's technical direction and drive execution in partnership with technical leads. Provide technical mentorship, and review designs and code to maintain high engineering quality.
Collaborate closely with engineers, product managers, scientists, and Operations to drive clarity, alignment, and delivery of high-impact solutions to complex business problems.
Own projects end-to-end, from ideation and design through production rollout and iteration, and drive measurable business impact across teams.

View full posting on CareerOneStop → ID: 942f0f7266aa

Senior Software Engineer, Machine Learning Infrastructure and Quality

Apple · Seattle, WA

Senior Doctorate

2026-05-19

WA 2026-05-19

Requirements

5+ years of experience with hardware and/or software development lifecycle processes
5+years of experience in one or more compiled languages (e.g. C, C++, Objective-C/Swift)
Proficient in one or more scripting languages e.g. Python, Go, or JavaScript
Experience with Machine Learning, its common practical applications, and commonly used frameworks
Proven understanding of Operating System concepts
Proven ability crafting, maintaining and implementing tests plans across all application layers
Applying statistical concepts to validate and QA data and models
QA and automation experience involving ML workflows is a huge plus
Posses the capability to accept ambiguity and deliver extraordinary results on tight schedules
B.S., M.S., or Ph.D. in Computer Engineering, Electrical Engineering, Computer Science, or equivalent experience

Preferred

5+years using one of the following scripting languages e.g. Python, Go, or JavaScript
5+years of experience working with an building Operating Systems

Responsibilities

The cloudOS team is responsible for all facets of delivering OS and system services on Apple silicon servers, including driving hardware and software initiatives to enable new Apple silicon-based systems in data centers.
Our Apple Services Engineering team is hiring for an exciting new role as a Senior Software Engineer in Machine learning. We are seeking a highly motivated and detail oriented software engineer to drive innovations in software development and quality for various machine learning workflows. The right candidate for this position is passionate about delivering the best possible experience for our users and is continuously looking for new ways to measure and improve the quality of our software stack and infrastructure. Additionally, having the ability to switch between designing creative product usage scenarios and immersive analysis of detailed feature design will be a critical skill to possess.
This is a full time Software Developer position where you will be driving working on various aspects of machine learning including training, inference, and characterization for various ML workloads. You will also be responsible to define, measure, and improve the quality of machine learning technologies at Apple by developing infrastructure, automation and services which facilitate validation and qualification of these technologies. In addition, you will be responsible for developing and implementing comprehensive automated test plans. You will be working cross-functionally with many teams across Apple impacting all levels of the Apple's machine learning stack. You will be the voice of our customers, championing quality software development through each step of the development process and driving quality improvements throughout the organization.

View full posting on CareerOneStop → ID: 9861140895b9

Sr Data Scientist, WWSO Bedrock

Amazon · Seattle, WA

Senior Bachelor's

2026-05-19

WA 2026-05-19

Requirements

5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
4+ years of data scientist experience
Experience with statistical models e.g. multinomial logistic regression
5+ years of management of technical, enterprise customer facing resources or equivalent experience
7+ years design/implementation/consulting experience of distributed applications
5+ years of hands-on experience with AI/ML or related technology domain
3+ years of hands-on experience with Responsible AI

Preferred

2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
Experience managing data pipelines
Experience as a leader and mentor on a data science team
Experience architecting, migrating, transforming or modernizing customer requirements to the cloud
Experience with presentations and speaking with executives, IT, management, and developers
BS degree in computer science or equivalent, or 4+ years of technical work experience
History of successful technical consulting and/or architecture engagements with large-scale customers or enterprises
Track record of thought leadership and innovation around Responsible AI.

Responsibilities

Customer Advisor- Implement, and deploy state of the art machine learning algorithms under Gen AI. You will build prototypes, troubleshoot customer issues, and explore new solutions. You will interact closely with our customers and with the academic community.
Thought Leadership - Evangelize AWS features relating to Responsible AI and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.
Partner with SAs, Sales, Business Development and the AI/ML Service teams to accelerate customer adoption and providing guidance on their customer engagements.
Develop and support an AWS internal community of ML related subject matter experts worldwide. Create field enablement materials for the broader SA population, to help them understand how to integrate Amazon Web Services GenAI solutions into customer architectures.

View full posting on CareerOneStop → ID: 6848b7bbe5b6

AI/ML Engineer - Associate Consultant

Slalom LLC · Seattle, WA

Entry-level

2026-05-18

WA 2026-05-18

Responsibilities

AI/ML Engineer - Associate Consultant
Who You'll Work With
As a modern technology company, Slalom's technologists bring the art of the possible to life for our clients. Our Data + AI capability focuses on delivering next-generation AI and Machine Learning solutions that solve complex business challenges. You'll join a diverse team of engineers, data scientists, and AI thought leaders, working across modern AI platforms and partnering with leading technology providers.
In this role, you will also collaborate closely with business stakeholders and transformation leaders to drive adoption of Generative AI solutions, helping clients translate AI capabilities into real-world impact through coaching, enablement, and change management.
AI/ML Solution Development (Core - ~70%)
Apply Machine Learning, Generative AI, and LLM-based techniques to solve real business problems.
Design, develop, and support delivery of AI/ML solutions (e.g., NLP, recommendation systems, agentic workflows).
Build and deploy AI solutions leveraging modern cloud platforms (AWS, Azure, GCP).
Implement best practices in MLOps / LLMOps, model validation, and production deployment.
Contribute to solution architecture discussions and technical delivery across client engagements.
Stay current on emerging AI/ML trends and contribute to Slalom's AI community through knowledge sharing.
AI Coaching & Adoption (Differentiator - ~30%)
Coach client teams on effective and responsible use of Generative AI tools (e.g., ChatGPT, copilots, custom AI solutions).
Deliver enablement sessions and workshops to drive AI literacy and adoption.
Partner with business stakeholders to identify high-value AI use cases and translate them into technical solutions.
Support organizational change efforts tied to AI adoption, including workflow redesign and user enablement.
Develop reusable assets, playbooks, and

View full posting on CareerOneStop → ID: da0d24af5d5e

AI/ML Engineer - Consultant

Slalom LLC · Seattle, WA

Mid-level

2026-05-18

WA 2026-05-18

Responsibilities

AI/ML Engineer - Consultant
Who You'll Work With
As a modern technology company, Slalom's technologists bring the art of the possible to life for our clients. Our Data + AI capability focuses on delivering next-generation AI and Machine Learning solutions that solve complex business challenges. You'll join a diverse team of engineers, data scientists, and AI thought leaders, working across modern AI platforms and partnering with leading technology providers.
In this role, you will also collaborate closely with business stakeholders and transformation leaders to drive adoption of Generative AI solutions, helping clients translate AI capabilities into real-world impact through coaching, enablement, and change management.
AI/ML Solution Development (Core - ~70%)
Apply Machine Learning, Generative AI, and LLM-based techniques to solve real business problems.
Design, develop, and support delivery of AI/ML solutions (e.g., NLP, recommendation systems, agentic workflows).
Build and deploy AI solutions leveraging modern cloud platforms (AWS, Azure, GCP).
Implement best practices in MLOps / LLMOps, model validation, and production deployment.
Contribute to solution architecture discussions and technical delivery across client engagements.
Stay current on emerging AI/ML trends and contribute to Slalom's AI community through knowledge sharing.
AI Coaching & Adoption (Differentiator - ~30%)
Coach client teams on effective and responsible use of Generative AI tools (e.g., ChatGPT, copilots, custom AI solutions).
Deliver enablement sessions and workshops to drive AI literacy and adoption.
Partner with business stakeholders to identify high-value AI use cases and translate them into technical solutions.
Support organizational change efforts tied to AI adoption, including workflow redesign and user enablement.
Develop reusable assets, playbooks, and best pract

View full posting on CareerOneStop → ID: bed40b2057a2

AI and Machine Learning Assistant Professor/Professional Pra

UTAH STATE UNIVERSITY · Logan, UT

Mid-level Doctorate

2026-05-18

ID 2026-05-18

Requirements

An earned doctorate degree in Electrical Engineering, Computer Engineering, Computer Science, Mathematics, Statistics, or a closely related discipline.
An ability to conduct and disseminate research that applies AI/ML to problems in the electrical engineering domain.
An ability to develop courses in AI/ML and effectively teach undergraduate and graduate level courses in AI/ML and the candidate's specific area of research emphasis in accordance with departmental needs.
An ability to apply for and secure ongoing external funding.
An earned MS degree in Electrical Engineering, Computer Engineering, Computer Science, Mathematics, Statistics, or equivalent work experience.
Strong industrial, commercial, consulting, or research experience in AI/ML systems.
An... For full info follow application link.

Preferred

Preference will be given to candidates with experience building and deploying AI/ML systems.

Responsibilities

Successful candidates for the tenure-track position will be expected to develop an externally funded research program that includes peer-reviewed publications and graduate student mentorship. Both tenure-track and professional practice positions are expected to effectively teach undergraduate and graduate courses, actively participate in assigned department and university duties, and serve their professional society. Ideal candidates will have an interest in developing new courses and degree programs in AI/ML and its applications to engineering.

View full posting on CareerOneStop → ID: a313763fc548

Sr Engineer, Machine Learning Engineering

T-Mobile USA, Inc · Bellevue, WA

Senior Master's

2026-05-17

WA 2026-05-17

Education

Bachelor's Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Required)
Master's/Advanced Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Preferred)
1+ year of experience in designing, developing, and deploying large language models (LLMs) and generative AI systems in production environments (Required)
5+ years of experience building and maintaining end-to-end ML pipelines, including data ingestion, training, deployment, monitoring, and optimization (Required)
3+ years of experience applying MLOps practices and leveraging cloud platforms (AWS, GCP, or Azure) for scalable AI solutions (Required)
Experience implementing fine-tuning, evaluation, and benchmarking techniques for LLMs and generative AI applications (Preferred)
5+ years of experience collaborating with cross-functional teams (engineering, data scienc

Responsibilities

The Senior Engineer, Machine Learning plays a pivotal role in advancing AI capabilities, focusing on the design, development, and deployment of large language models (LLMs) and generative AI solutions. This position is essential for building scalable, production-grade AI systems that enable automation, personalization, and intelligent decision-making across the enterprise. The role emphasizes the creation of innovative GenAI applications that deliver real-world business impact while maintaining high standards of performance, reliability, and responsible AI practices. Collaborating with cross-functional technical teams, they ensure the seamless integration of LLM-powered solutions into products and workflows, reinforcing the organization's leadership in applying advanced AI technologies.
Build and manage the complete machine learning and generative AI lifecycle, including research, design, experimentation, development, deployment, monitoring, and maintenance.
Design, develop, and deploy LLM-based and generative AI models to power scalable and intelligent enterprise applications.
Architect, optimize, and maintain retrieval-augmented generation (RAG), prompt orchestration, and contextual reasoning pipelines to support diverse AI use cases.
Implement scalable MLOps pipelines for model deployment, performance monitoring, and continuous improvement.
Conduct fine-tuning, alignment, and evaluation of LLMs and multimodal models to ensure reliability, efficiency, and fairness.
Collaborate with data science, engineering, and product teams to translate business needs into generative AI-driven solutions.
Perform benchmarking, evaluation, and optimization of generative models to improve accuracy, latency, and cost efficiency.
Research and apply emerging techniques in transformer architectures, multimodal learning, and generative modeling to drive innovation and enhance enterprise capabilities.
Ensure secure, ethical, and responsible AI deployment, embedding fairness, transparency, and compliance throughout the model lifecycle.
Mentor and guide team members on generative AI frameworks, best practices, and experimentation methodologies.
Participate in other duties or projects as assigned by business management as needed.

View full posting on CareerOneStop → ID: 6fbcb19eb395

Sr. Data Scientist, Enterprise Security Products

Amazon · Seattle, WA

Senior

2026-05-17

WA 2026-05-17

Requirements

6+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
5+ years of data scientist experience
Experience with statistical models e.g. multinomial logistic regression

Preferred

2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
Experience managing data pipelines
Experience as a leader and mentor on a data science team

Responsibilities

Build the intelligence behind AI-first security products: Design, train, and ship ML models that power agentic systems, anomaly detection, threat classification, and automated response - all running across multi-cloud environments.
Own the full science lifecycle: From problem framing and data exploration through model development, evaluation, production deployment, and monitoring. You build it, you ship it, you run it.
Build with AI to build AI: Use agentic coding tools, LLM-powered workflows, and experimental AI tooling to accelerate every phase of your work; from EDA to feature engineering to model iteration. Multiply your velocity and raise the bar for what one scientist can deliver.
Power agentic architectures: Develop the models, embeddings, RAG pipelines, evaluation frameworks, and feedback loops that make multi-agent security systems smart, safe, and customer-ready.
Prototype rapidly and validate with customers: Turn hypotheses into prototypes in days, not quarters. Iterate based on real customer signal and ship what works.
Partner across disciplines: Work directly with SDEs, applied scientists, security researchers, PMs, and UX designers to turn ambiguous problems into shipped solutions. Small team means short lines between you and the decision.
Communicate with impact: Translate complex modeling results into clear recommendations for engineers, product leaders, and senior executives. Influence direction with data.
Raise the science bar: Contribute to technical and science reviews, mentor teammates, and champion AI-first development practices. Help shape the science culture of a fast-growing team from the ground floor.
No two days look the same on this fast-growing, AI-first team. You might start your morning reviewing evaluation results from overnight model training runs, then dive into building a RAG pipeline or tuning a multi-agent orchestration loop. Before lunch, you're pair-prompting with an agentic coding assistant to stand up a new feature pipeline. In the afternoon, you join a design session with senior and principal scientists and engineers where your ideas carry weight regardless of title. You own science problems end to end, ship using the latest AI-assisted workflows, and see your models reach production fast. This is where builders thrive.

View full posting on CareerOneStop → ID: 3d85ab5de8ae

Clinical Data Scientist

Baylor Scott & White Health · Boise, ID

Mid-level

2026-05-16

ID 2026-05-16

View full posting on CareerOneStop → ID: 7754aa13e25a

Clinical Data Scientist

Baylor Scott & White Health · Salem, OR

Mid-level

2026-05-16

OR 2026-05-16

View full posting on CareerOneStop → ID: d7cc39d9e068

Associate Data Scientist

Capgemini · Seattle, WA

Entry-level

2026-05-16

WA 2026-05-16

Requirements

Design, develop, and deploy AI enabled applications aligned to enterprise needs.
Translate business problems into scalable technical solutions.
Build Generative AI solutions using large language models, including RAG and tool enabled workflows.
Apply AI assisted code generation and developer productivity tools for tasks such as code scaffolding, refactoring, documentation, and test generation.
Design and integrate application components using REST APIs, authentication, error handling, and observability best practices.
Deploy and operate AI solutions in production or production adjacent environments, supporting monitoring and reliability.
The base compensation range for this role in the posted location is $70,000 - $110,000
Contract Type: Permanent
Seattle, WA, US
Brand: Capgemini
Professional Community: Data & AI

Responsibilities

Capgemini is building a Seattle-based AI Cohort to support strategic enterprise engagements focused on Generative AI, intelligent applications, and advanced analytics. This role combines hands-on AI engineering with a delivery and consulting oriented mindset. You will work closely with business and technical stakeholders to shape, build, and scale AI solutions from early exploration through production delivery. Some engagements may follow a Forward Deployment Engineer (FDE)-style working model, where engineers collaborate closely with client teams during solution design and rollout. However, the role remains broad and well suited for candidates who enjoy combining strong technical problem solving with collaborative, client facing delivery. Many initiatives are centered on enterprise cloud and AI platforms, with a strong preference for Azure based architectures and services, as well as modern developer environments that incorporate AI assisted development and code generation tools.

View full posting on CareerOneStop → ID: 27df4a92a606

Sr Data Scientist- Consumer Analytics

T-Mobile USA, Inc · Bellevue, WA

Senior Master's

2026-05-16

WA 2026-05-16

Education

Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience (Required)
Acceptable areas of study include Quantitative Discipline (math, statistics, economics, computer science, physics, engineering, etc.) (Required)
4-7 years Industry experience in predictive modeling, data science, and analysis in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models (Required)
4-7 years Experience with data scripting languages (e.g., SQL, Python, R) (Required)
2-4 years Experience with big data architecture and pipeline, Hadoop, Hive, Spark, Kafka, etc. (Required)
4-7 years Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data (Required)
4-7 years Experience in data visualization (Required)
4-7 years Experience working with relational database using SQL (Required)
2-4 years Experience in the telecom industry (Preferred)
*Knowledge, Skills and Abilities:
Mathematics Calculus, linear algebra, statistics, and probability (Required)
Programming Expertise in Python and SQL (Required)
Machine Learning: Expertise applying machine learning concepts and techniques related to supervised and unsupervised learning (Required)
At least 18 years of age
Legally authorized to work in the United States
*Travel:Travel Required (Yes/No): NoDOT Regulated:DOT Regulated Position (Yes/No): NoSafety Sensitive Position (Yes/No): No
Base Pay Range: $106,000 - $191,100

Responsibilities

This role leads the application of machine learning techniques and statistical methods to address complex business challenges effectively. It involves collaborating with diverse technical and non-technical stakeholders to deliver data-driven solutions. The role requires expertise across the entire machine learning lifecycle, including problem framing, data collection, model development, deployment, and performance evaluation. Success is measured by the ability to create actionable insights and deploy models that drive informed decision-making and business value. The work impacts organizational outcomes by transforming data into strategic assets that support business objectives and customer needs.
Extract and model large, complex data sets using machine learning, mathematics, statistics, and programming to generate predictive insights
Deliver timely, high-quality analysis and actionable recommendations that support intelligent business decision-making
Provide senior-level guidance and mentorship by reviewing projects, models, and code to support team development
Collaborate with engineering teams to implement and enhance machine learning pipelines and production-ready models
Communicate key information and insights to business leaders through verbal, written, and data visualization methods
Also responsible for other duties/projects as assigned by business management as needed

View full posting on CareerOneStop → ID: 10389d929b61

Staff Data Scientist, Product

Google · Kirkland, WA

Senior Master's

2026-05-16

WA 2026-05-16

Requirements

Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
10 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 8 years work experience plus a Master's degree).

Preferred

Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
12 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).

Responsibilities

Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.
Google is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. At Google, engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.
The US base salary range for this full-time position is $192,000-$278,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Provide analytical thought leadership through proactive and strategic contributions (e.g., suggests new analyses, infrastructure or experiments to drive improvements in the business).
Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, and implementation of analytical/statistical models, and presentation to stakeholders.
Develop solutions, lead, and manage problems that may be ambiguous and lacking clear precedent by framing problems, generating hypotheses, and making recommendations from a perspective that combines both, analytical and product-specific expertise.
Oversee the integration of cross-functional and cross-organizational project/process timelines, develop process improvements and recommendations, and help define operational goals and objectives.
Directly or indirectly oversee the contributions of others and develop colleagues' capabilities in the area of specialization.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 87b6f7a2eaef

Technical Program Manager II, Data Center Planning, Machine Learning

Google · Kirkland, WA

Manager Bachelor's

2026-05-16

WA 2026-05-16

Requirements

Bachelor's degree in a technical field, or equivalent practical experience.
2 years of experience in program management.
Experience in one of the following planning areas (e.g., capacity planning, supply planning, demand planning, or data center planning).
Experience in data modeling and analysis.

Preferred

5 years of experience in capacity planning, strategic operations planning, data analytics, inventory optimization, or management/operations consulting.
2 years of experience managing cross-functional or cross-team projects.
Experience collaborating and influencing stakeholders spanning across multiple organizations and different levels of responsibilities.
Demonstrated ability to take complex, ambiguous topics and create compelling narratives and present them to leadership.
Ability to shift between direct detailed analysis and big picture thinking and customizing communication based on the audience.
Excellent data analysis skills (e.g., Sheets, SQL).

Responsibilities

A problem isn't truly solved until it's solved for all. That's why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you'll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You'll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.
The Data Center Planning organization is responsible for identifying the most cost-efficient set of data centers to meet a 5-year forecast demand signal and for identifying and planning the Product Areas (PAs) who will occupy them. We drive alignment on what we should build, where, when, and who may occupy it through the Building Demand Plan (BDP) and Earmarks, an extensive set of optimization processes which provides demand justification and outlook for capital funding of data centers. This in turn provides signals to the downstream partner teams to identify new supply options and expansion of current facilities and assets. Within DCP, the Demand and Allocation Planning team is responsible for developing and maintaining our end-to-end power plan of record and continuously seeking to deliver further optimization through extensive scenario planning. We provide key upstream and downstream partners with chase signals, driving the acquisition of additional capacity, configuration of facilities to support the latest ML chips, and even where we may need to shape demand between geographies.
Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
The US base salary range for this full-time position is $138,000-$198,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Offer clear, concise, and logical judgment and actionable recommendations to partners and executives in a timely manner regarding Google's data center capacity needs.
Use data to identify planning solutions and provide advice to business leaders across the organization.
Codify, maintain, and update Google PAs' technical and business requirements in partnership with Product Area Resource Managers (PARMs), and use them to influence execution and Google's spend and capacity allocation decisions.
Implement new DC power planning initiatives, including automation with engineering support and cross-functional policy changes.
Work with the customer to manage and resolve all DC capacity related issues and escalations.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 19e4e76090b4

Technical Program Manager III, Machine Learning, Google Cloud

Google · Kirkland, WA

Manager Doctorate

2026-05-16

WA 2026-05-16

Requirements

Bachelor's degree in a relevant field, or equivalent practical experience.
5 years of experience in program management.
Experience working with data structures or machine learning algorithms.

Preferred

Master's degree, PhD, or equivalent experience in Engineering, Computer Science, or other technical related field.
5 years of experience managing cross-functional or cross-team projects.
3 years of experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, or deep learning.

Responsibilities

A problem isn't truly solved until it's solved for all. That's why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you'll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You'll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.
Using your extensive technical and leadership expertise, you'll manage projects of various size and scope, identifying future opportunities, improving processes and driving the technical directions of your programs.
Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
The US base salary range for this full-time position is $163,000-$237,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Provide software development and project management, coordination, and inter/intra team communications to deliver outstanding program outcomes.
Work closely with Software Engineers, QA, Product Managers and other engineering teams to get high-quality products and features through the software project lifecycle (build, test and release on time).
Manage project schedules, identify possible issues and clearly communicate them to project stakeholders.
Lead several technical programs for Google Cloud, setting priorities for products and engineering, leading teams to take products to market, assuring success metrics are informing future efforts, and quickly fine tuning the program as needed.
Exercise knowledge of data structures or algorithms that improve software performance over time. Build, maintain and enhance business, operational, and management dashboards
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 87cede07c68e

Post Bachelor's Research Associate - AI & Data Science for National Security

Pacific Northwest National Laboratory · Richland, WA

Entry-level Bachelor's

2026-05-16

WA 2026-05-16

Requirements

Candidates must have received a Bachelor's degree within the past 24 months or within the next 8 months from an accredited college or university.
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Degree in Computer Science, Data Science, Statistics, or Applied Mathematics.
Experience programming in Python; AI/ML packages like PyTorch, computer vision libraries (torchvision, PIL), AWS integrations (SageMaker, S3, boto3), message queues (Kafka) and database languages such as SQL.
Experience with production systems or working in operationally-focused environments.
Comfort working across a full cloud-based pipeline from research to implementation and testing to deployment.
Previous experience as intern supporting the National Security domain at a National Laboratory.

Responsibilities

Innovate and operationalize multimodal AI/ML solutions, integrating radiographic analysis, text processing, and real-time sensor information to address challenges in national security.
Drive impactful results from research to operational deployment, translating technical work into immediate real-world impact through direct integration with active systems and in presentation form to diverse audiences with varied technical backgrounds.
Ensure the reproducibility and documentation of all code and analytical pipelines to support a high standard of scientific and technical rigor, including GitOps practices, managing infrastructure and application code via version control.
Own research direction and drive independent initiative, in this setting decisions and outcomes directly shape operational systems protecting national borders.

View full posting on CareerOneStop → ID: 18f78758e1cb

AI Data Scientist Sr.

Sedgwick · Boise, ID

Senior

2026-05-15

ID 2026-05-15

View full posting on CareerOneStop → ID: 093121240dae

Data Science Manager

Maximus · Boise, ID

Manager Bachelor's

2026-05-15

ID 2026-05-15

Requirements

'- Bachelor's Degree in related field.
5-7 years of relevant professional experience required.
Leadership skills with formal training and/or prior experience.
Programming Languages: SQL, Python, R.
Cloud Based DBMS: Snowflake, Amazon RDS (Oracle, SQL Server, MySQL), MongoDB, etc.
Experience with big data, including structured, semi-structured, and unstructured data.
Experience with machine learning, specifically in the domain of natural language processing (NLP).

Responsibilities

Oversee the ongoing developments and operations of a high-performing Data Science, Reporting, and Business Analysis team, providing vision, guidance, and mentorship to staff.
Compile and evaluate data to improve operations process or quality.
Assist with special projects, trend analysis, and problem-solving. Provide support to operational teams on issues that need deep dives to improve process, efficiency, or errors.
Establish a vision for productization of data science artifacts and delivering Data Science as a Service.
Work with reporting and business analyst to interpret/translate various datasets to tell a story to business partners and senior leadership team.
Assist in compiling, creating, and managing reporting.
Drive team alignment with key objectives that align with organizational and project goals.
Collect, arrange, and inspect data using various tools to create required reports.
Act as the primary liaison between project operational groups and client stakeholders, driving cross-functional alignment, elevating transparency across key stakeholder groups.
Collect, analyze, and interpret data into actionable opportunities for improvement.
Identify appropriate decision technology techniques to apply to relevant analytic frameworks.
Develop/maintain a consistent and cohesive reporting structure delivering regular data, reporting, and analysis to a variety of key stakeholders.
Specialize in performing research and analysis to devise strategies for optimal business operations and services, ensuring efficiency and increased productivity. Manage Business Analysts performance, determine priority, schedule according to business needs.
Gather & analyze data; Perform data discovery, analysis and modeling; Troubleshooting & problem-solving to support operations; root cause analysis, process improvement plans; reporting; deep dive into staffing, WFM, or operational issues.
Assist with project management; Collaborate with managers to meet operational expectations. Provide assistance with required and ad hoc reporting.
Prepare progress reports and presentations, updating databases as needed, maintain records and documentation.
Maintain reporting structures, ensuring reports are being delivered timely and accurately. Track, report, and communicate trends, error rates, or other business requests by operational leaders.
Oversight of provisioning/deprovisioning processes, working with Ops to ensure readiness for new hires.

View full posting on CareerOneStop → ID: be3e4ab14d9d

Director, Data Science

Norstella · Boise, ID

Director Doctorate

2026-05-15

ID 2026-05-15

Requirements

10+ years of experience developing and deploying AI/ML applications and delivering data-driven solutions at scale
Demonstrated experience leading and managing data science teams, including hiring, performance management, and talent development
Proven track record of building and scaling high-performing teams - including designing leveling frameworks, mentorship programs, and succession planning
Deep hands-on expertise in Generative AI, Large Language Models (LLMs), Agentic AI systems, and advanced NLP/Deep Learning techniques
Practical experience with LLM application design: prompt engineering, retrieval-augmented generation (RAG), model fine-tuning, tool use, and multi-agent orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen)
Graduate degree (Master's or PhD) in Computer Science, Engineering, Statistics, or a related quantitative discipline, or equivalent professional experience
Strong command of Python and core data science libraries (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow)
Deep understanding of CS fundamentals, computational complexity, and algorithm design
Experience architecting and delivering large-scale distributed systems in an agile environment, including rapid prototyping and iterative development
Excellent communication and stakeholder management skills - able to translate complex technical concepts for executive and non-technical audiences

Preferred

PhD in Computer Science with an AI/ML research focus and publications in top-tier venues
Experience in the healthcare or life sciences domain; familiarity with applying AI to pharmaceutical or market access data
Hands-on experience with AWS ML infrastructure: SageMaker, Lambda, S3, Snowflake, and related services
Experience with knowledge graphs, structured reasoning, and hybrid retrieval architectures
Prior experience operating at Director level or equivalent in a fast-paced, data-driven organization

Responsibilities

As Director of Data Science at Norstella, you will set the strategic vision for our data science capabilities and lead a high-performing team of data scientists and engineers. You will be a technical authority and a people-first leader - building talent, shaping culture, and delivering AI-powered solutions that have a direct impact on patient access to life-saving therapies.
Define and own the data science strategy, aligning closely with product, engineering, and executive leadership to drive roadmap prioritization
Lead, mentor, and grow a team of data scientists and ML engineers - fostering a culture of excellence, curiosity, and continuous learning
Build and develop talent: recruit top-tier data science professionals, design career development frameworks, and create pathways for growth at all levels
Champion the adoption of GenAI, Agentic AI, and LLM-powered architectures across the organization - defining reference frameworks for tool use, code interpretation, retrieval-augmented generation (RAG), and multi-agent workflows
Collaborate with product leadership to identify, elaborate, and prioritize high-impact projects
Oversee the delivery of AI-enabled microservices in collaboration with content and product engineering teams
Define and evolve engineering standards, best practices, and architectural patterns for scalable, production-grade AI systems
Stay at the cutting edge of AI/ML research; deliver regular presentations to internal stakeholders on emerging trends and their strategic implications
Partner cross-functionally to ensure data science solutions are operationalized effectively and drive measurable business value
All other duties, as assigned.

View full posting on CareerOneStop → ID: 6593366915af

Data Science Manager

Maximus · Salem, OR

Manager Bachelor's

2026-05-15

OR 2026-05-15

Requirements

'- Bachelor's Degree in related field.
5-7 years of relevant professional experience required.
Leadership skills with formal training and/or prior experience.
Programming Languages: SQL, Python, R.
Cloud Based DBMS: Snowflake, Amazon RDS (Oracle, SQL Server, MySQL), MongoDB, etc.
Experience with big data, including structured, semi-structured, and unstructured data.
Experience with machine learning, specifically in the domain of natural language processing (NLP).

Responsibilities

Oversee the ongoing developments and operations of a high-performing Data Science, Reporting, and Business Analysis team, providing vision, guidance, and mentorship to staff.
Compile and evaluate data to improve operations process or quality.
Assist with special projects, trend analysis, and problem-solving. Provide support to operational teams on issues that need deep dives to improve process, efficiency, or errors.
Establish a vision for productization of data science artifacts and delivering Data Science as a Service.
Work with reporting and business analyst to interpret/translate various datasets to tell a story to business partners and senior leadership team.
Assist in compiling, creating, and managing reporting.
Drive team alignment with key objectives that align with organizational and project goals.
Collect, arrange, and inspect data using various tools to create required reports.
Act as the primary liaison between project operational groups and client stakeholders, driving cross-functional alignment, elevating transparency across key stakeholder groups.
Collect, analyze, and interpret data into actionable opportunities for improvement.
Identify appropriate decision technology techniques to apply to relevant analytic frameworks.
Develop/maintain a consistent and cohesive reporting structure delivering regular data, reporting, and analysis to a variety of key stakeholders.
Specialize in performing research and analysis to devise strategies for optimal business operations and services, ensuring efficiency and increased productivity. Manage Business Analysts performance, determine priority, schedule according to business needs.
Gather & analyze data; Perform data discovery, analysis and modeling; Troubleshooting & problem-solving to support operations; root cause analysis, process improvement plans; reporting; deep dive into staffing, WFM, or operational issues.
Assist with project management; Collaborate with managers to meet operational expectations. Provide assistance with required and ad hoc reporting.
Prepare progress reports and presentations, updating databases as needed, maintain records and documentation.
Maintain reporting structures, ensuring reports are being delivered timely and accurately. Track, report, and communicate trends, error rates, or other business requests by operational leaders.
Oversight of provisioning/deprovisioning processes, working with Ops to ensure readiness for new hires.

View full posting on CareerOneStop → ID: ce74020e7d03

Director, Data Science

Norstella · Salem, OR

Director Doctorate

2026-05-15

OR 2026-05-15

Requirements

10+ years of experience developing and deploying AI/ML applications and delivering data-driven solutions at scale
Demonstrated experience leading and managing data science teams, including hiring, performance management, and talent development
Proven track record of building and scaling high-performing teams - including designing leveling frameworks, mentorship programs, and succession planning
Deep hands-on expertise in Generative AI, Large Language Models (LLMs), Agentic AI systems, and advanced NLP/Deep Learning techniques
Practical experience with LLM application design: prompt engineering, retrieval-augmented generation (RAG), model fine-tuning, tool use, and multi-agent orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen)
Graduate degree (Master's or PhD) in Computer Science, Engineering, Statistics, or a related quantitative discipline, or equivalent professional experience
Strong command of Python and core data science libraries (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow)
Deep understanding of CS fundamentals, computational complexity, and algorithm design
Experience architecting and delivering large-scale distributed systems in an agile environment, including rapid prototyping and iterative development
Excellent communication and stakeholder management skills - able to translate complex technical concepts for executive and non-technical audiences

Preferred

PhD in Computer Science with an AI/ML research focus and publications in top-tier venues
Experience in the healthcare or life sciences domain; familiarity with applying AI to pharmaceutical or market access data
Hands-on experience with AWS ML infrastructure: SageMaker, Lambda, S3, Snowflake, and related services
Experience with knowledge graphs, structured reasoning, and hybrid retrieval architectures
Prior experience operating at Director level or equivalent in a fast-paced, data-driven organization

Responsibilities

As Director of Data Science at Norstella, you will set the strategic vision for our data science capabilities and lead a high-performing team of data scientists and engineers. You will be a technical authority and a people-first leader - building talent, shaping culture, and delivering AI-powered solutions that have a direct impact on patient access to life-saving therapies.
Define and own the data science strategy, aligning closely with product, engineering, and executive leadership to drive roadmap prioritization
Lead, mentor, and grow a team of data scientists and ML engineers - fostering a culture of excellence, curiosity, and continuous learning
Build and develop talent: recruit top-tier data science professionals, design career development frameworks, and create pathways for growth at all levels
Champion the adoption of GenAI, Agentic AI, and LLM-powered architectures across the organization - defining reference frameworks for tool use, code interpretation, retrieval-augmented generation (RAG), and multi-agent workflows
Collaborate with product leadership to identify, elaborate, and prioritize high-impact projects
Oversee the delivery of AI-enabled microservices in collaboration with content and product engineering teams
Define and evolve engineering standards, best practices, and architectural patterns for scalable, production-grade AI systems
Stay at the cutting edge of AI/ML research; deliver regular presentations to internal stakeholders on emerging trends and their strategic implications
Partner cross-functionally to ensure data science solutions are operationalized effectively and drive measurable business value
All other duties, as assigned.

View full posting on CareerOneStop → ID: 53e9df0c11dc

Data Scientist , Prime Video - Advertising

Amazon · Seattle, WA

Mid-level

2026-05-15

WA 2026-05-15

Requirements

5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
4+ years of data scientist experience
Experience with statistical models e.g. multinomial logistic regression
Experience with statistical methods (e.g., A/B Testing, Regression)

Preferred

2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
Experience managing data pipelines
Experience as a leader and mentor on a data science team

Responsibilities

Use advanced statistical and machine learning techniques to extract insights from large-scale streaming, ad delivery, and auction data sets.
Design and implement end-to-end data science workflows from data acquisition and cleaning through model development, offline evaluation, A/B testing, and production deployment in partnership with product and engineering teams
Build, validate, and maintain the statistical models that support the roadmap including Supply tier classification and Supply Quality Index, ad tolerance and fatigue scoring, and propensity and disengagement prediction
Partner with product and economist teams to design hold out experiments to measure impact of Ad load on revenue and customer engagement; define north star metrics, power calculations, holdout structures, and promotion gates for every major lever.
Support scalable, self-service analytics by building curated datasets for PVa product, ops, sales, and science covering supply, yield, CX, and advertiser diversification outcomes.
Partner with product stakeholders and science peers to identify strategic, data-driven opportunities to improve the customer experience and advertiser results.
Communicate findings, conclusions, and recommendations to technical and non-technical stakeholders
Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organization

View full posting on CareerOneStop → ID: 90d212c981a9

Data Scientist, Core Experimentation

OpenAI Inc. · Seattle, WA

Mid-level

2026-05-15

WA 2026-05-15

Responsibilities

We are hiring a Staff-level Data Scientist to help lead the evolution of OpenAI's core experimentation platform. This role is focused on improving the statistical rigor, reliability, and practical usability of experimentation across the company.
You'll work on some of the hardest problems in online experimentation: sample ratio mismatch detection, variance reduction, bias mitigation, metric design, triggered analysis, heterogeneous treatment effects, sequential testing, and experimentation in complex ML systems. You'll also help translate advanced statistical concepts into pragmatic systems and product experiences that teams can actually use.
This is a highly technical individual contributor role with significant influence across methodology, platform architecture, and experimentation best practices. The ideal candidate combines deep statistical expertise with strong systems intuition and hands-on experience building or operating experimentation platforms at scale.
*In this role, you will:
Drive the statistical direction and technical strategy for OpenAI's experimentation platform
Design and improve experimentation methodologies used across product and research teams
Build pragmatic solutions to real-world experimentation challenges, balancing rigor with operational simplicity
Improve the reliability and trustworthiness of experiment results, including detection and prevention of bias, logging issues, and data quality failures
Developscalable analytical systems and pipelines in Python and distributed compute environments
Partner with engineers and product teams to improve experiment design, metric quality, and decision-making practices
Lead investigations into complex experimentation anomalies and measurement failures
Establish best practices for experimentation governance, interpretation, and statistical correctness
Mentor other data scientists and raising the overall technical bar for experimentation and causal inference
*You might thrive in this role if you have:
Experience building, scaling, or operating experimentation platforms at a large technology company
Deep expertise in statistics, causal inference, and online experimentation methodology
Strong understanding of practical experimentation challenges in production systems
Experience with areas such as variance reduction, CUPED, sequential testing, SRM detection, metric design, or heterogeneous effects
Strong coding and systems skills in Python and large-scale data processing frameworks (e.g. Spark)
Experience designing analytical data models and scalable experimentation pipelines
Ability to communicate complex statistical concepts clearly to technical and non-technical audiences
Track record of influencing technical strategy through hands-on technical leadership
Experience in large-scale product experimentation, ML experimentation, ranking system

View full posting on CareerOneStop → ID: e024f1d95905

Language Data Scientist, Alexa International

Amazon · Bellevue, WA

Mid-level Doctorate

2026-05-15

WA 2026-05-15

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of guiding and coaching a group of researchers experience
1+ years of working with or evaluating AI systems experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree or above in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Experience applying theoretical models in an applied environment

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

To be successful in this role, you must have a passion for data, efficiency, and accuracy. Specifically, you will:
Own data analyses for customer-facing features, including launch go/no-go metrics for new features and accuracy metrics for existing features
Handle unique data analysis requests from a range of stakeholders, including quantitative and qualitative analyses to elevate customer experience with speech interfaces
Lead and evaluate changing dialog evaluation conventions, test tooling developments, and pilot processes to support expansion to new data areas
Continuously evaluate workflow tools and processes and offer solutions to ensure they are efficient, high quality, and scalable
Provide expert support for a large and growing team of data analysts
Provide support for ongoing and new data collection efforts as a subject matter expert on conventions and use of the data
Conduct research studies to understand speech and customer-Alexa interactions
Collaborate with scientists and product managers, and other stakeholders in defining and validating customer experience metrics

View full posting on CareerOneStop → ID: eaa6ee5d0b4b

Senior Staff Research Data Scientist, Workspace GenAI

Google · Seattle, WA

Senior Doctorate

2026-05-15

WA 2026-05-15

Requirements

Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.

Preferred

12 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 10 years of work experience with a PhD degree.

Responsibilities

Empower the Google Workspace ecosystem with intelligent capabilities including Gmail, Docs, and Meet by delivering actionable insights and defining the critical metrics that drive quality and high-impact organizational opportunities.
The US base salary range for this full-time position is $262,000-$365,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Provide high-level technical direction for the Workspace Data Science (WDS) GenAI Foundations team, fostering a culture of rapid experimentation and leading the organization through complex technical transitions.
Utilize AI models and tools as integral components for evaluating, synthesizing, and understanding complex datasets.
Develop new methodologies to improve the performance of Google's models through better training data, including data acquisition, and insights.
Drive Data Science-led horizontal experimentation and evaluation across key components of the Workspace GenAI Platform.
Act as a technical partner, collaborating closely with Research, Engineering, and Product teams (Workspace and Google DeepMind).
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 1f27c26d673b

Senior Staff Research Data Scientist, Workspace GenAI

Google · Kirkland, WA

Senior Doctorate

2026-05-15

WA 2026-05-15

Requirements

Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.

Preferred

12 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 10 years of work experience with a PhD degree.

Responsibilities

Empower the Google Workspace ecosystem with intelligent capabilities including Gmail, Docs, and Meet by delivering actionable insights and defining the critical metrics that drive quality and high-impact organizational opportunities.
The US base salary range for this full-time position is $262,000-$365,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Provide high-level technical direction for the Workspace Data Science (WDS) GenAI Foundations team, fostering a culture of rapid experimentation and leading the organization through complex technical transitions.
Utilize AI models and tools as integral components for evaluating, synthesizing, and understanding complex datasets.
Develop new methodologies to improve the performance of Google's models through better training data, including data acquisition, and insights.
Drive Data Science-led horizontal experimentation and evaluation across key components of the Workspace GenAI Platform.
Act as a technical partner, collaborating closely with Research, Engineering, and Product teams (Workspace and Google DeepMind).
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 5c9398ec2222

Sr. Staff AI/ML Engineer

WEX INC · Seattle, WA

Senior Master's

2026-05-15

WA 2026-05-15

Requirements

12+ years of professional software or ML engineering experience, with a track record of deploying production-grade AI systems.
Proficiency in Python and key machine learning frameworks (PyTorch, TensorFlow, or similar).
Strong working knowledge of core libraries (NumPy, Pandas, scikit-learn) and LLM development frameworks (LangChain, ADK, or similar).
Experience with cloud platforms (AWS preferred; Azure or GCP also valuable) and Infrastructure-as-Code tools like Terraform.
Deep familiarity with CI/CD pipelines and DevOps practices using GitHub Actions or similar platforms.
Demonstrated ability to operate in agile, collaborative, high-trust teams.
Bachelor's degree in Computer Science, Engineering, or a related discipline (Master's preferred).
Bonus: Experience in financial systems, data compliance, or building multi-tenant Agentic AI applications.
You'll work within

Responsibilities

Location:This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; Dallas, TX; San Francisco Bay Area, CA; and Seattle/WA.
AI Platform Engineering, WEX Inc.
Lead the design, implementation, and production deployment of machine learning and AI-driven systems-including LLM-based and agentic applications.
Partner with AI platform and product engineering teams to integrate advanced AI capabilities into WEX's enterprise systems.
Design and maintain ML pipelines, from data ingestion to model deployment, ensuring scalability, observability, and reusability across teams.
Build and expose AI functionality via RESTful APIs and micro-services architectures.
Champion engineering best practices: CI/CD, infrastructure-as-code, testing automation, and continuous improvement.
Contribute to architectural decisions with a focus on security, compliance, and performance-especially in regulated industries such as payments and healthcare.
Collaborate cross-functionally with data scientists, ML engineers, and business stakeholders to align technical solutions with strategic goals.

View full posting on CareerOneStop → ID: 35ab92981071

Data Science Manager

Maximus · Olympia, WA

Manager Bachelor's

2026-05-15

WA 2026-05-15

Requirements

'- Bachelor's Degree in related field.
5-7 years of relevant professional experience required.
Leadership skills with formal training and/or prior experience.
Programming Languages: SQL, Python, R.
Cloud Based DBMS: Snowflake, Amazon RDS (Oracle, SQL Server, MySQL), MongoDB, etc.
Experience with big data, including structured, semi-structured, and unstructured data.
Experience with machine learning, specifically in the domain of natural language processing (NLP).

Responsibilities

Oversee the ongoing developments and operations of a high-performing Data Science, Reporting, and Business Analysis team, providing vision, guidance, and mentorship to staff.
Compile and evaluate data to improve operations process or quality.
Assist with special projects, trend analysis, and problem-solving. Provide support to operational teams on issues that need deep dives to improve process, efficiency, or errors.
Establish a vision for productization of data science artifacts and delivering Data Science as a Service.
Work with reporting and business analyst to interpret/translate various datasets to tell a story to business partners and senior leadership team.
Assist in compiling, creating, and managing reporting.
Drive team alignment with key objectives that align with organizational and project goals.
Collect, arrange, and inspect data using various tools to create required reports.
Act as the primary liaison between project operational groups and client stakeholders, driving cross-functional alignment, elevating transparency across key stakeholder groups.
Collect, analyze, and interpret data into actionable opportunities for improvement.
Identify appropriate decision technology techniques to apply to relevant analytic frameworks.
Develop/maintain a consistent and cohesive reporting structure delivering regular data, reporting, and analysis to a variety of key stakeholders.
Specialize in performing research and analysis to devise strategies for optimal business operations and services, ensuring efficiency and increased productivity. Manage Business Analysts performance, determine priority, schedule according to business needs.
Gather & analyze data; Perform data discovery, analysis and modeling; Troubleshooting & problem-solving to support operations; root cause analysis, process improvement plans; reporting; deep dive into staffing, WFM, or operational issues.
Assist with project management; Collaborate with managers to meet operational expectations. Provide assistance with required and ad hoc reporting.
Prepare progress reports and presentations, updating databases as needed, maintain records and documentation.
Maintain reporting structures, ensuring reports are being delivered timely and accurately. Track, report, and communicate trends, error rates, or other business requests by operational leaders.
Oversight of provisioning/deprovisioning processes, working with Ops to ensure readiness for new hires.

View full posting on CareerOneStop → ID: 30584effbdd7

Director, Data Science

Norstella · Olympia, WA

Director Doctorate

2026-05-15

WA 2026-05-15

Requirements

10+ years of experience developing and deploying AI/ML applications and delivering data-driven solutions at scale
Demonstrated experience leading and managing data science teams, including hiring, performance management, and talent development
Proven track record of building and scaling high-performing teams - including designing leveling frameworks, mentorship programs, and succession planning
Deep hands-on expertise in Generative AI, Large Language Models (LLMs), Agentic AI systems, and advanced NLP/Deep Learning techniques
Practical experience with LLM application design: prompt engineering, retrieval-augmented generation (RAG), model fine-tuning, tool use, and multi-agent orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen)
Graduate degree (Master's or PhD) in Computer Science, Engineering, Statistics, or a related quantitative discipline, or equivalent professional experience
Strong command of Python and core data science libraries (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow)
Deep understanding of CS fundamentals, computational complexity, and algorithm design
Experience architecting and delivering large-scale distributed systems in an agile environment, including rapid prototyping and iterative development
Excellent communication and stakeholder management skills - able to translate complex technical concepts for executive and non-technical audiences

Preferred

PhD in Computer Science with an AI/ML research focus and publications in top-tier venues
Experience in the healthcare or life sciences domain; familiarity with applying AI to pharmaceutical or market access data
Hands-on experience with AWS ML infrastructure: SageMaker, Lambda, S3, Snowflake, and related services
Experience with knowledge graphs, structured reasoning, and hybrid retrieval architectures
Prior experience operating at Director level or equivalent in a fast-paced, data-driven organization

Responsibilities

As Director of Data Science at Norstella, you will set the strategic vision for our data science capabilities and lead a high-performing team of data scientists and engineers. You will be a technical authority and a people-first leader - building talent, shaping culture, and delivering AI-powered solutions that have a direct impact on patient access to life-saving therapies.
Define and own the data science strategy, aligning closely with product, engineering, and executive leadership to drive roadmap prioritization
Lead, mentor, and grow a team of data scientists and ML engineers - fostering a culture of excellence, curiosity, and continuous learning
Build and develop talent: recruit top-tier data science professionals, design career development frameworks, and create pathways for growth at all levels
Champion the adoption of GenAI, Agentic AI, and LLM-powered architectures across the organization - defining reference frameworks for tool use, code interpretation, retrieval-augmented generation (RAG), and multi-agent workflows
Collaborate with product leadership to identify, elaborate, and prioritize high-impact projects
Oversee the delivery of AI-enabled microservices in collaboration with content and product engineering teams
Define and evolve engineering standards, best practices, and architectural patterns for scalable, production-grade AI systems
Stay at the cutting edge of AI/ML research; deliver regular presentations to internal stakeholders on emerging trends and their strategic implications
Partner cross-functionally to ensure data science solutions are operationalized effectively and drive measurable business value
All other duties, as assigned.

View full posting on CareerOneStop → ID: 3149ede13fe7

Data Science Manager

Maximus · Helena, MT

Manager

2026-05-15

MT 2026-05-15

View full posting on CareerOneStop → ID: 8d1a0cfa10ff

Director, Data Science

Norstella · Helena, MT

Director

2026-05-15

MT 2026-05-15

View full posting on CareerOneStop → ID: f8062d67e1f8

AI Data Scientist Sr.

Sedgwick · Missoula, MT

Senior

2026-05-15

MT 2026-05-15

View full posting on CareerOneStop → ID: cc89b63d0b01

AI Data Scientist Sr.

Sedgwick · Seattle, WA

Senior

2026-05-15

WA 2026-05-15

View full posting on CareerOneStop → ID: 67258d999a8e

AI Data Scientist Sr.

Sedgwick · Olympia, WA

Senior

2026-05-15

WA 2026-05-15

View full posting on CareerOneStop → ID: e7c3bdbd38dc

AI Data Scientist Sr.

Sedgwick · Spokane, WA

Senior

2026-05-15

WA 2026-05-15

View full posting on CareerOneStop → ID: 7fc62ef510bd

AI Data Scientist Sr.

Sedgwick · Portland, OR

Senior

2026-05-15

WA 2026-05-15

View full posting on CareerOneStop → ID: a345aaa56e39

AI Data Scientist Sr.

Sedgwick · Salem, OR

Senior

2026-05-15

OR 2026-05-15

View full posting on CareerOneStop → ID: 1ad1445af1d9

Senior Data Scientist - GenAI/Python/AWS/SQL

Unum Group · Boise, ID

Senior Doctorate

2026-05-14

ID 2026-05-14

Requirements

6+ years of professional experience or equivalent relevant work.
Proven track record leading end-to-end data science projects with measurable business impact.
*Technical Expertise
*Core Data Science Capabilities (expert in at least two, strong in others):
Programming & Automation:
Python required; experience with automation, DevOps practices, APIs, file I/O, and database integrations.
Experience engineering solutions in cloud environments (AWS preferred; Azure/Google comparable).
Exposure to object-oriented development and scalable architecture.
Data Visualization:
Expertise across multiple visualization tools and techniques.
Ability to tailor visuals to business use cases and audiences.
Statistics & Machine Learning:
Deep knowledge of statistical inference, regression, feature selection, feature extraction, and ML algorithms.
Experience leading large-scale modeling projects end-to-end.
Familiarity with generative AI approaches is a plus.
Data Engineering / ETL:
Strong SQL skills; ability to design, debug, and optimize complex queries.
Ability to navigate and explore large databases independently.
Experience combining internal and external data sources.
*Soft Skills & Business Leadership
Strong communication skills, including the ability to influence senior leaders.
Project management expertise and strong business acumen (financial services experience a plus).
Ability to manage multiple concurrent initiatives in a fast-moving environment.
Comfortable leading engagements and representing analytics with executive leadership.

Education

Bachelor's degree in a quantitative field required.
Master's or PhD in a quantitative discipline preferred.

Responsibilities

*Analytical Solution Development
Design, develop, and execute analytical solutions using optimization, simulation, machine learning, generative AI, and statistical modeling.
Construct predictive models to explain events, forecast behaviors, identify risk, or perform segmentation and clustering.
Apply domain expertise to ensure models are practical, interpretable, and aligned with business needs.
Evaluate alternative approaches and select appropriate modeling techniques for each use case.
*Data Engineering & Preparation
Integrate and transform large volumes of data from diverse sources (e.g., DB2, SQL Server, Teradata, APIs) to support analytics and experimentation.
Build modeling-ready datasets using validation, reconciliation, feature engineering, and aggregation techniques.
Write complex SQL queries involving multi-table joins, data exploration, and troubleshooting with minimal guidance.
Develop logical data models combining internal and external datasets; lead conversations with external data providers when needed.
*Automation & Deployment
Build automated analytics pipelines leveraging scripting, APIs, DevOps practices, and cloud platforms.
Partner with engineering and IT teams to scale solutions, automate workflows, and integrate models into business processes.
Play a lead role in operationalizing AI/ML solutions within production environments.
*Visualization, Insights & Communication
Develop and deliver clear, compelling visualizations (static or dynamic) tailored to various audiences.
Interpret analytical results and communicate actionable insights that influence senior leaders and key business partners.
Translate complex technical work into business-friendly recommendations.
*Leadership, Mentorship & Collaboration
Coach, mentor, and develop junior data scientists; provide technical guidance and feedback.
Provide leadership on data science initiatives, ensuring outputs meet quality standards.
Work in a collaborative, innovation-focused environment with product owners, engineers, data architects, and business partners.
Manage multiple projects simultaneously, prioritizing independently and guiding less experienced team members.
*Innovation & Research
Stay current on emerging statistical methods, machine learning advancements, and generative AI tools.
Conduct independent R&D to prototype new approaches and explore innovative solutions for high-visibility business problems.
Demonstrate entrepreneurial, self-starter mindset with a strong curiosity and continuous-learning orientation.
Unum and Colonial Life are part of Unum Group, a Fortune 500 company and leading provider of employee benefits to companies worldwide. Headquartered in Chattanooga, TN, with international offices in Ireland, Poland and the UK, Unum also has significant operations in Portland, ME, and Baton Rouge, LA - plus over 35 US field offices. Colonial Life is headquartered in Columbia, SC, with over 40 field offices nationwide.

View full posting on CareerOneStop → ID: 317cead46060

Senior Data Scientist - GenAI/Python/AWS/SQL

Unum Group · Salem, OR

Senior Doctorate

2026-05-14

OR 2026-05-14

Requirements

6+ years of professional experience or equivalent relevant work.
Proven track record leading end-to-end data science projects with measurable business impact.
*Technical Expertise
*Core Data Science Capabilities (expert in at least two, strong in others):
Programming & Automation:
Python required; experience with automation, DevOps practices, APIs, file I/O, and database integrations.
Experience engineering solutions in cloud environments (AWS preferred; Azure/Google comparable).
Exposure to object-oriented development and scalable architecture.
Data Visualization:
Expertise across multiple visualization tools and techniques.
Ability to tailor visuals to business use cases and audiences.
Statistics & Machine Learning:
Deep knowledge of statistical inference, regression, feature selection, feature extraction, and ML algorithms.
Experience leading large-scale modeling projects end-to-end.
Familiarity with generative AI approaches is a plus.
Data Engineering / ETL:
Strong SQL skills; ability to design, debug, and optimize complex queries.
Ability to navigate and explore large databases independently.
Experience combining internal and external data sources.
*Soft Skills & Business Leadership
Strong communication skills, including the ability to influence senior leaders.
Project management expertise and strong business acumen (financial services experience a plus).
Ability to manage multiple concurrent initiatives in a fast-moving environment.
Comfortable leading engagements and representing analytics with executive leadership.

Education

Bachelor's degree in a quantitative field required.
Master's or PhD in a quantitative discipline preferred.

Responsibilities

*Analytical Solution Development
Design, develop, and execute analytical solutions using optimization, simulation, machine learning, generative AI, and statistical modeling.
Construct predictive models to explain events, forecast behaviors, identify risk, or perform segmentation and clustering.
Apply domain expertise to ensure models are practical, interpretable, and aligned with business needs.
Evaluate alternative approaches and select appropriate modeling techniques for each use case.
*Data Engineering & Preparation
Integrate and transform large volumes of data from diverse sources (e.g., DB2, SQL Server, Teradata, APIs) to support analytics and experimentation.
Build modeling-ready datasets using validation, reconciliation, feature engineering, and aggregation techniques.
Write complex SQL queries involving multi-table joins, data exploration, and troubleshooting with minimal guidance.
Develop logical data models combining internal and external datasets; lead conversations with external data providers when needed.
*Automation & Deployment
Build automated analytics pipelines leveraging scripting, APIs, DevOps practices, and cloud platforms.
Partner with engineering and IT teams to scale solutions, automate workflows, and integrate models into business processes.
Play a lead role in operationalizing AI/ML solutions within production environments.
*Visualization, Insights & Communication
Develop and deliver clear, compelling visualizations (static or dynamic) tailored to various audiences.
Interpret analytical results and communicate actionable insights that influence senior leaders and key business partners.
Translate complex technical work into business-friendly recommendations.
*Leadership, Mentorship & Collaboration
Coach, mentor, and develop junior data scientists; provide technical guidance and feedback.
Provide leadership on data science initiatives, ensuring outputs meet quality standards.
Work in a collaborative, innovation-focused environment with product owners, engineers, data architects, and business partners.
Manage multiple projects simultaneously, prioritizing independently and guiding less experienced team members.
*Innovation & Research
Stay current on emerging statistical methods, machine learning advancements, and generative AI tools.
Conduct independent R&D to prototype new approaches and explore innovative solutions for high-visibility business problems.
Demonstrate entrepreneurial, self-starter mindset with a strong curiosity and continuous-learning orientation.
Unum and Colonial Life are part of Unum Group, a Fortune 500 company and leading provider of employee benefits to companies worldwide. Headquartered in Chattanooga, TN, with international offices in Ireland, Poland and the UK, Unum also has significant operations in Portland, ME, and Baton Rouge, LA - plus over 35 US field offices. Colonial Life is headquartered in Columbia, SC, with over 40 field offices nationwide.

View full posting on CareerOneStop → ID: 161ff9376ec3

Data Scientist (Data Science)

The Boeing Company · Seattle, WA

Mid-level Doctorate

2026-05-14

WA 2026-05-14

Requirements

Familiarity with GPU compute infrastructure and distributed model training.
Familiarity with container technologies (e.g., Docker, Kubernetes).
Shape the direction of generative AI in a mission-critical organization.
Collaborate with a world-class team of engineers, scientists, and domain experts.
Access to cutting-edge infrastructure, models, and research partnerships.
Bachelor's degree in computer science, Machine Learning, Applied Mathematics, Computer Engineering, Software Engineering, Artificial Intelligence, Physics or a closely related field.
3+ years of experience in data science or machine learning.
3+ years of experience in programming in Python and familiarity with data engineering workflows (e.g., Spark, Airflow, SQL).
This position must meet U.S. export control compliance requirements. To meet U.S. export control compliance requirements, a "U.S. Person" as defined by 22 C.F.R. §120.62 is required.
"U.S. Person" includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asylee.
*Export Control Details:
US based job, US Person required

Preferred

Master's or PhD in Computer Science, Machine Learning, Applied Mathematics, Computer Engineering, Software Engineering, Artificial Intelligence, Physics or a closely related field
Experience fine-tuning open-source models and integrating APIs from commercial providers.
Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
Experience in AI ethics and governance in generative models.
Experience with data engineering tools (e.g., SQL, Spark

Education

Education/experience typically acquired through advanced technical education (e.g. Bachelor) and typically 5 or more years' related work experience or an equivalent combination of technical education and experience (e.g. PhD, Master+3 years' related work experience, 9 years' related work experience, etc.).

Responsibilities

At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.
*Boeing Defense, Space & Security (BDS) has an exciting opportunity for a Mid-Level Data Scientist - GenAI to join our team located in Seattle, WA or Arlington, VA.
*We are seeking a skilled and innovative Data Scientist to contribute to the development and optimization of advanced AI, Machine Learning (ML), and Generative AI (GenAI) models within BDS. This role offers the opportunity to learn and grow your skills in ML and large language models (LLMs). You will work closely with senior data scientists and cross-functional teams to contribute to AI-driven applications in our organization.
*Successful candidates will have:
Proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow).
Contribute to the development and deployment of models.
Design and implement pipelines for model fine-tuning and evaluation.
Develop prompt engineering strategies and embedding techniques to enhance model performance.
Prototype applications that address specific business needs.
Assist in model performance evaluation and bias/fairness assessments.
Collaborate with MLOps and engineering teams to support model scaling and monitoring.
Share knowledge of AI/ML/GenAI tools and trends with the team and contribute to best practices.
*This position is hybrid. The selected candidate will be required to perform some work onsite at one of the listed location options. This is at the hiring team's discretion and could potentially change in the future.
*This position is for 1st shift.
*This position must meet export control compliance requirements. To meet export control compliance requirements, a "U.S. Person" as defined by 22 C.F.R. §120.15 is required. "U.S. Person" includes U.S. Citizen, lawful permanent resident, refugee, or asylee.

View full posting on CareerOneStop → ID: 7d65307bce22

Data Scientist - Research Informatics

Seattle Children's · Seattle, WA

Mid-level Master's

2026-05-14

WA 2026-05-14

Education

Bachelor's degree or higher in a STEM or relevant analytical field that demonstrates analytical and technical competency and 2+ years as a Data Analyst using data science tools and methods OR a Master's in a STEM or relevant analytical field that demonstrates analytical and technical competency with evidence of work or applied research experience using data science tools and methods.
Experience with statistics as well as machine learning/data mining/etc.
Experience developing and using statistical models and algorithms.
Intermediate or higher experience in least one major data science language (e.g., R, Python).
Experience in use of data visualization tools and methods.
Experience working with source control tools and version management.
Experience in data extraction using at least one data manipulation language/package(e.g., SQL, R-dplyr, SAS DATA step, Python-pandas).
Experience as a member of a delivery team supporting integrated data science products and solutions for a wide range of customer groups.
*Required Credentials

View full posting on CareerOneStop → ID: 2eeab0445572

Data Scientist, Amazon Devices, Devices Sales & Marketing

Amazon · Bellevue, WA

Mid-level Bachelor's

2026-05-14

WA 2026-05-14

Requirements

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data scientist experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Bachelor's degree
Experience applying theoretical models in an applied environment

Preferred

Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company

Responsibilities

The Amazon Devices organization designs, produces and markets Echo Speakers, Kindle e-readers, Fire Tablets, Fire TV Streaming Media Players, Ring and Blink Smart Home & Security products. We are constantly looking to innovate on behalf of customers with new devices in existing or new categories or improving customer experience on existing platforms. The Devices Data Services (DDS) team provides Data Science, Analytics and Engineering support to the broader organization to enable Sales and Marketing activities across all these product lines.
We are looking for an innovative, hands-on and customer-obsessed Data Scientist who can be a strategic partner to the product managers and engineers on the team. Our projects span multiple organizations and require coordination of experimentation, economic and causal analysis, and building predictive machine learning models. A successful candidate will be a problem solver who enjoys diving into data, is excited by difficult modeling challenges, is motivated to build something that will eventually become a production software system, and possesses strong communication skills to effectively interface between technical and business teams.
In this role, you will be a technical expert with massive impact. You will take the lead on developing
advanced ML systems that are key to reaching our customers with the right recommendations at the right time. Your work will directly impact the success of Amazon's growing Devices business. You will work across diverse science/engineering/business teams. You will work on critical data science problems, building high quality, reliable, accurate, and consistent code sets that are aligned with our business needs.
Key Performance Areas
Implement statistical or machine learning methods to solve specific business problems.
Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
Directly contribute to development of modern automated recommendation systems
Build customer-facing reporting tools to provide insights and metrics to track model performance and explain variance
Collaborate with researchers, software developers, and business leaders to define product requirements, provide analytical support, and communicate feedback
You will work with other scientists, engineers, product managers, and marketers to develop new products that benefit our customers and help us reach our business goals. You will own solutions from end to end: conceptualization, prioritization, development, delivery, and productionalization.

View full posting on CareerOneStop → ID: 505a54140149

Data Scientist, Senior

Booz Allen Hamilton INC. · Port Orchard, WA

Senior Bachelor's

2026-05-14

WA 2026-05-14

Job Number: R0239360 Data Scientist, Senior The Opportunity : As a data scientist, you're excited at the prospect of unlocking the secrets held by a data set, and you're fascinated by the possibilities presented by IoT, machine learning, and artifi cia l intelligence. In an i

View full posting on CareerOneStop → ID: d593361ab7a0

Machine Learning - Compiler Engineer II, Annapurna Labs

Amazon · Seattle, WA

Mid-level Doctorate

2026-05-14

WA 2026-05-14

Requirements

3+ years of non-internship professional software development experience
2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
Experience programming with at least one software programming language
3+ years of non-internship professional software development, or 3+ years of software development experience
2+ years of experience architecting and optimizing compilers
Proficiency with 1 or more of the following programming languages: C++ (preferred), C, Python

Preferred

3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Bachelor's degree in computer science or equivalent
PhD in computer science, computer engineering, or related field, or MS degree
Experience with multiple toolchains and Instruction Set Architectures
Proficiency with resource management, scheduling, code generation, and compute graph optimization
Experience optimizing Tensorflow, PyTorch or MxNET deep learning models

View full posting on CareerOneStop → ID: a724fa94a580

Machine Learning Engineer, Ad Response Prediction

Amazon · Seattle, WA

Mid-level Bachelor's

2026-05-14

WA 2026-05-14

Requirements

3+ years of non-internship professional software development experience
3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
2+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
Knowledge of machine learning model architecture and inference

Preferred

Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT
1+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
Experience developing, deploying and managing AI products at scale

Responsibilities

Own technical vision and direction - Identify problems, develop solutions, and embrace performance metrics to assess system health
Build and grow your team - Wear many hats (software design, implementation, project management, operations, business partnerships) and grow leaders within your group
Collaborate on product direction - Build strong relationships across engineering, Product, UX, and QA to deliver the right product for customers
Lead beyond your team - Contribute to a growing community of engineering leaders, sharing experience and technical acumen to drive org-wide technology decisions
Own your own shop - Our products reach hundreds of millions of customers globally; services must meet high standards for operational excellence (24x7x365)
Highly analytical - You solve problems backed by verifiable data, driving processes, tools, and statistical methods that support rational decision-making
Team obsessed - You grow team members, foster creative atmospheres for innovation, and hold engineers accountable for smart decisions and results
Humbitious - Ambitious yet humble; you use introspection and feedback to continuously raise the ba
Engaged by ambiguity - You explore new problem spaces with unique constraints and non-obvious solutions, quickly identifying gaps and the right people to fill them

View full posting on CareerOneStop → ID: 2a7c3a205fdf

Principal Machine Learning Engineer- Search Quality

Snowflake Inc. · Clyde Hill, WA

Senior

2026-05-14

WA 2026-05-14

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don't just use tools; you possess an innate curiosity, treating AI as a high-trust collabora

View full posting on CareerOneStop → ID: 1f493482cec9

Senior Machine Learning Engineer - Earner Incentive

Uber · Seattle, WA

Senior Doctorate

2026-05-14

WA 2026-05-14

Requirements

Ph.D., M.S., or Bachelor's degree in Computer Science, Statistics, Mathematics, Machine Learning, Operations Research, or a related field, or equivalent practical experience with demonstrated impact.
5+ years of experience across the end-to-end ML lifecycle, including data analysis, feature engineering, model development, deployment, monitoring, and iteration in large-scale production systems. Proven ability to deliver measurable business impact and strong understanding of MLOps best practices.
Strong understanding of a broad range of ML and statistical techniques, including deep learning (e.g., multi-task learning, transformers), tree-based models, and classical approaches, with solid judgment in selecting methods based on context and data.
Proficiency in at least one production language (Python, Scala, Java, or Go) and common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
Solid software engineering skills, including system design, writing and reviewing production-quality code, testing, and operating ML systems in production.
Strong ownership, learning mindset, collaboration and communication skills; able to work independently and effectively in cross-functional teams.

Preferred

Experience developing and deploying pricing, matching, or incentive algorithms for two-sided marketplaces, with strong product intuition and system-level thinking.
Experience with multi-armed bandits, reinforcement learning, and causal ML, including applying these methods in production systems.
Familiarity with large-scale data and ML infrastructure (e.g. Spark, Flink), and batch or real-time data processing systems.
Strong communication and leadership skills, with the ability to lead initiatives, prototype quickly, drive alignment, and collaborate effectively with cross-functional partners, from early idea generation through productionization.
Experience leading complex technical projects, influencing scope, technical direction, and execution across multiple engineers or teams.
Ability to translate ambiguous business problems into clear, actionable problem statements, define success metrics, and drive execution through well-reasoned trade-offs.
Demonstrated technical leadership, such as mentoring engineers, leading cross-functional efforts, or shaping ML / optimization strategy.
Experience designing, running and analyzing large-scale online experiments to prove impact, interpret results, guide decision-making, and translate insights into concrete product or system changes.
For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Responsibilities

Uber's Marketplace is at the core of the business. The Earner Incentive team in Marketplace builds products and systems that empower drivers through targeted incentives, creating a more balanced and efficient marketplace while enhancing engagement and experience.
The team owns the end-to-end incentive lifecycle, from ML-driven incentive generation to scalable online serving, answering questions such as who, where, when, how, and how much, powered by large-scale machine learning, optimization, and experimentation systems . These systems enable proactive, targeted incentives that shape supply, optimize earnings, and guide marketplace balance.
We are seeking a Senior Machine Learning Engineer to design and scale the technical foundations behind Uber's driver incentive systems. You will develop and productionize large-scale ML models and decision systems that power both scheduled and near real-time, intelligent incentive generation and delivery at Uber's global scale.
In this role, you will collaborate closely with engineers, product managers, operations, and scientists to set technical direction, make thoughtful trade-offs, and turn complex problems into reliable production systems. Your work will directly shape how incentives are designed and delivered at scale, enhancing marketplace efficiency and reliability, and empowering earning opportunities for millions of drivers worldwide.
*What the Candidate Will Do
Design, develop, productionize, and operate end-to-end ML solutions and data pipelines for large-scale systems that power driver incentives.
Develop and apply advanced ML and optimization techniques to design incentive mechanisms for online marketplaces, improving marketplace efficiency and reliability while enabling earning opportunities for millions of drivers.
Build deep domain expertise in incentives, pricing, and marketplace dynamics, and understand how these systems interact with Operations. Translate business requirements into clear problem statements and actionable technical plans, reasoning through trade-offs to deliver practical, production-ready solutions.
Help set the team's technical direction and drive execution in partnership with technical leads. Provide technical mentorship, and review designs and code to maintain high engineering quality.
Collaborate closely with engineers, product managers, scientists, and Operations to drive clarity, alignment, and delivery of high-impact solutions to complex business problems.
Own projects end-to-end, from ideation and design through production rollout and iteration, and drive measurable business impact across teams.

View full posting on CareerOneStop → ID: 83b706309cd7

Senior Machine Learning Engineer, Rider (Multiple Teams)

Uber · Seattle, WA

Senior Doctorate

2026-05-14

WA 2026-05-14

Requirements

Bachelor's degree in Computer Science, Engineering, Mathematics or related field
3+ years of experience in software engineering with an emphasis on data-driven methodologies, deep learning, and online experimentation
Strong problem-solving skills, with expertise in ML methodologies
Experience in applying ML, statistics, or optimization techniques to solve large-scale real-world problems (e.g. ads tech, recommender systems)
Industry experience in ML frameworks (e.g. Tensorflow, Pytorch, or JAX) and complex data pipelines; programming languages such as Python, Spark SQL, Presto, Java, Go

Preferred

5+ years of experience in software engineering specializing in applied ML methods
Experience in designing and crafting scalable, reliable, maintainable and reusable ML solutions using deep-learning techniques and statistical methods.
Innate truth-seeker who values and produces analytic evidence and insight, as well as translating them and business goals into technical problems and solutions.
Experience with deep-learning techniques, having worked with embeddings and transformer architectures
1+ years of experience working in a cross-functional and/or cross-business projects, partnering with Product, Scientists, and cross-org leads to shape the team's strategies
Passionate about helping junior members grow by inspiring and mentoring engineers
Resilience, determination, ownership mindset
PhD degree in Computer Science, Engineering, Mathematics or related field
For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Responsibilities

Defining and driving ML solutions for key strategic problems in the space of product recommendations and merchandising: help riders find and complete rides with the right products, understanding their ride context and modeling their intent while attending to Uber's business goals, marketplace conditions and efficiencies.
Provide technical leadership to a passionate, experienced, and diverse engineering team. Manage project priorities, deadlines and deliverables and design, develop, test, deploy and maintain ML solutions. Classification, regression, and multi-task learning are in our toolbox.
Raise the bar of ML engineering by improving best practices, producing exemplary code, documentation, automated tests and thorough & precise monitoring, and applying model debugging & interpretation techniques.
Partner with product owners, data scientists and business teams to translate key insights and business opportunities into technical solutions

View full posting on CareerOneStop → ID: 24562ed79fec

Senior Principal Machine Learning Engineer, Ad Platforms

The Walt Disney Company · Seattle, WA

Senior Doctorate

2026-05-14

WA 2026-05-14

Requirements

BS or MS in Computer Science/Engineering or relevant work experience
12+ years of software engineering experience
Demonstrable analytical / problem-solving / design skills in a highly distributed and highly available services ecosystem
Strong foundations in algorithms, data structures, and numerical optimization with experience in programming languages such as Python (primary), Java and SQL
Experience with tools and frameworks such as TensorFlow, Pytorch, Hugging Face libraries
Model optimization and inference (TensorRT, ONNX, DeepSpeed)
Ad Tech Industry knowledge
Deep expertise in:
LLMs and OpenAI GPT models, Claude, Gemini, Llama, and similar models.
Fine-tuning (SFT, PEFT, RLHF, adapters)
Prompt engineering, retrieval-augmented generation (RAG), context management, and multi-agent systems and MCPs
Embeddings, and vector search

Preferred

PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field
The hiring range for this position in Santa Monica, CA is $228,700 - $306,700 per year and in Seattle is $239,700 - $321,400. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
*Job ID: 10150390

Responsibilities

Ad Platforms is responsible for Disney's industry-leading ad technology and products - driving advertising performance, innovation, and value in Disney's sports, news, and entertainment content, across all media platforms.
As our team's Sr Principal Machine Learning Engineer (IC leadership role), you will apply your industry-tested experience, deep technical knowledge of software and systems including Machine Learning and AI patterns, platforms and infrastructure, and leadership skills to unblock and guide our ML and Research teams to create scalable, performant, maintainable, and testable models and pipelines.
*Daily, you should bring:
Excellent communication and collaboration across teams and organizations.
Strong and sound understanding of architectural best practices and principles in machine learning and AI domains
Proficiency in designing and implementing robust, scalable, measurable models and pipelines.
A passion for mentoring and learning in a very dynamic and fast-paced environment
Proven ability to collaborate with Product and Sales teams, translating requirements into well-defined technical implementations. Skilled in defining technical and operational metrics for measuring system health.
Knowledge of relevant and upcoming technologies and their potential application within the stack.
A keen eye for potential optimizations and enhancements
Kindness and pragmatic optimism.
Your unique view and experience.
A full toolkit of influence models and clear evidence based decision making methods
Reviewing designs and implementations for best practices
Influence on multi-year technical roadmap
Cross-org impact
Shaping product/business strategy
Part of the Architecture Guild within Ad Platforms
Reading requirements documentation from Product, translating into areas of work and partnering with team leads through execution as needed.
Exploring, researching, implementing proofs-of-concept, and proposing solutions that will reduce cost and overhead, improve maintainability, minimize the time features take to be in production.
Defining, reviewing, and documenting software and models in a high throughput, low latency environment.
Mentoring and inspiring team members in all aspects of professional software development.
Support on call activities with the MLP and Research teams
Establishing shared technical standards and working practices across globally distributed ML teams.

View full posting on CareerOneStop → ID: f429bfaa9d81

Senior Data Scientist - GenAI/Python/AWS/SQL

Unum Group · Olympia, WA

Senior Doctorate

2026-05-14

WA 2026-05-14

Requirements

6+ years of professional experience or equivalent relevant work.
Proven track record leading end-to-end data science projects with measurable business impact.
*Technical Expertise
*Core Data Science Capabilities (expert in at least two, strong in others):
Programming & Automation:
Python required; experience with automation, DevOps practices, APIs, file I/O, and database integrations.
Experience engineering solutions in cloud environments (AWS preferred; Azure/Google comparable).
Exposure to object-oriented development and scalable architecture.
Data Visualization:
Expertise across multiple visualization tools and techniques.
Ability to tailor visuals to business use cases and audiences.
Statistics & Machine Learning:
Deep knowledge of statistical inference, regression, feature selection, feature extraction, and ML algorithms.
Experience leading large-scale modeling projects end-to-end.
Familiarity with generative AI approaches is a plus.
Data Engineering / ETL:
Strong SQL skills; ability to design, debug, and optimize complex queries.
Ability to navigate and explore large databases independently.
Experience combining internal and external data sources.
*Soft Skills & Business Leadership
Strong communication skills, including the ability to influence senior leaders.
Project management expertise and strong business acumen (financial services experience a plus).
Ability to manage multiple concurrent initiatives in a fast-moving environment.
Comfortable leading engagements and representing analytics with executive leadership.

Education

Bachelor's degree in a quantitative field required.
Master's or PhD in a quantitative discipline preferred.

Responsibilities

*Analytical Solution Development
Design, develop, and execute analytical solutions using optimization, simulation, machine learning, generative AI, and statistical modeling.
Construct predictive models to explain events, forecast behaviors, identify risk, or perform segmentation and clustering.
Apply domain expertise to ensure models are practical, interpretable, and aligned with business needs.
Evaluate alternative approaches and select appropriate modeling techniques for each use case.
*Data Engineering & Preparation
Integrate and transform large volumes of data from diverse sources (e.g., DB2, SQL Server, Teradata, APIs) to support analytics and experimentation.
Build modeling-ready datasets using validation, reconciliation, feature engineering, and aggregation techniques.
Write complex SQL queries involving multi-table joins, data exploration, and troubleshooting with minimal guidance.
Develop logical data models combining internal and external datasets; lead conversations with external data providers when needed.
*Automation & Deployment
Build automated analytics pipelines leveraging scripting, APIs, DevOps practices, and cloud platforms.
Partner with engineering and IT teams to scale solutions, automate workflows, and integrate models into business processes.
Play a lead role in operationalizing AI/ML solutions within production environments.
*Visualization, Insights & Communication
Develop and deliver clear, compelling visualizations (static or dynamic) tailored to various audiences.
Interpret analytical results and communicate actionable insights that influence senior leaders and key business partners.
Translate complex technical work into business-friendly recommendations.
*Leadership, Mentorship & Collaboration
Coach, mentor, and develop junior data scientists; provide technical guidance and feedback.
Provide leadership on data science initiatives, ensuring outputs meet quality standards.
Work in a collaborative, innovation-focused environment with product owners, engineers, data architects, and business partners.
Manage multiple projects simultaneously, prioritizing independently and guiding less experienced team members.
*Innovation & Research
Stay current on emerging statistical methods, machine learning advancements, and generative AI tools.
Conduct independent R&D to prototype new approaches and explore innovative solutions for high-visibility business problems.
Demonstrate entrepreneurial, self-starter mindset with a strong curiosity and continuous-learning orientation.
Unum and Colonial Life are part of Unum Group, a Fortune 500 company and leading provider of employee benefits to companies worldwide. Headquartered in Chattanooga, TN, with international offices in Ireland, Poland and the UK, Unum also has significant operations in Portland, ME, and Baton Rouge, LA - plus over 35 US field offices. Colonial Life is headquartered in Columbia, SC, with over 40 field offices nationwide.

View full posting on CareerOneStop → ID: 179636388101

Senior Data Scientist - GenAI/Python/AWS/SQL

Unum Group · Helena, MT

Senior

2026-05-14

MT 2026-05-14

View full posting on CareerOneStop → ID: 21c10058896c

Machine Learning Engineer II, Pricing

Uber · Seattle, WA

Mid-level Doctorate

2026-05-13

WA 2026-05-13

Requirements

Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
2+ years of experience in developing and deploying machine learning models and optimization algorithms in large-scale production environments
Proficiency in programming languages such as Python, Scala, Java, or Go
Experience with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
Experience in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
Familiarity with modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. LP, convex optimization), combined with proven ability and ambition to continuously deepen expertise in these areas

Preferred

Experience in translating ambiguous business problems into technical solutions in a structured and principled way
Strong communication skills, including through documentation and design discussions
Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavio
Experience in reinforcement learning and causal machine learning
For New York, NY-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Responsibilities

Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders.
We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.
*What You Will Do
Design, develop, and productionize end-to-end ML solutions for large-scale distributed systems serving billions of trips
Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
Partner with senior engineers to plan the scope and execution of projects and mentor junior team members on design and implementation
Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

View full posting on CareerOneStop → ID: c8b958526340

Machine Learning Engineer, Ad Response Prediction

Amazon · Seattle, WA

Mid-level Bachelor's

2026-05-13

WA 2026-05-13

Requirements

3+ years of non-internship professional software development experience
3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
2+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
Knowledge of machine learning model architecture and inference

Preferred

Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT
1+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
Experience developing, deploying and managing AI products at scale

Responsibilities

Own technical vision and direction - Identify problems, develop solutions, and embrace performance metrics to assess system health
Build and grow your team - Wear many hats (software design, implementation, project management, operations, business partnerships) and grow leaders within your group
Collaborate on product direction - Build strong relationships across engineering, Product, UX, and QA to deliver the right product for customers
Lead beyond your team - Contribute to a growing community of engineering leaders, sharing experience and technical acumen to drive org-wide technology decisions
Own your own shop - Our products reach hundreds of millions of customers globally; services must meet high standards for operational excellence (24x7x365)
Highly analytical - You solve problems backed by verifiable data, driving processes, tools, and statistical methods that support rational decision-making
Team obsessed - You grow team members, foster creative atmospheres for innovation, and hold engineers accountable for smart decisions and results
Humbitious - Ambitious yet humble; you use introspection and feedback to continuously raise the ba
Engaged by ambiguity - You explore new problem spaces with unique constraints and non-obvious solutions, quickly identifying gaps and the right people to fill them

View full posting on CareerOneStop → ID: 10037c1d3b1f

Senior Data Scientist , Alexa AI Aurora

Amazon · Bellevue, WA

Senior

2026-05-13

WA 2026-05-13

Requirements

5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
4+ years of data scientist experience
Experience with statistical models e.g. multinomial logistic regression

Preferred

Experience managing data pipelines
Experience as a leader and mentor on a data science team

Responsibilities

Define the data science strategy for conversation modelling, content generation, and automated quality assurance by evaluating a wide range of methodologies across machine learning, generative AI, and computer vision, recommending the right approach based on business needs and scientific rigor.
Lead the design and end-to-end delivery of complex, ambiguous data science initiatives from problem formulation through experimentation to production deployment, autonomously defining the problem space, selecting ideal solution approaches, and driving measurable business outcomes.
Make high-judgment trade-offs across audio, text, and visual quality dimensions, balancing short-term customer needs against long-term platform extensibility, cost efficiency, and scalability while quantifying the impact of each decision.
Establish evaluation frameworks, metrics, and success criteria for the team's scientific initiatives, identifying blind spots in existing measurements and proposing new mechanisms that institutionalize rigorous validation across customer touch points.
Identify new business opportunities by staying at the forefront of AI/ML advances, translating emerging techniques into actionable data science directions with clear, quantifiable customer and business impact.
Drive consensus across multiple teams on the architectural and methodological decisions underlying scalable agentic systems for conversation understanding and generation, ensuring alignment between data, software systems, and business processes.
Set and continuously raise the bar for data science best practices across the team, creating models and analyses that are actionable, reproducible, and easy for others to contribute to and extend.
Tackle the team's most complex technical problems, applying broad expertise across multiple data science disciplines while maintaining practical focus on solution generalizability and customer value.
Actively mentor and develop other data scientists in the organization, leading scientific reviews, providing constructive feedback on methodology and results, and keeping the team current on data science advancements.
Advance the team's scientific reputation through high-impact publications and presentations at top-tier venues, and generate intellectual property through patents.

View full posting on CareerOneStop → ID: 172b46db2f27

Senior Machine Learning Manager, Search & Knowledge Platform

Apple · Seattle, WA

Manager Doctorate

2026-05-13

WA 2026-05-13

Requirements

8+ years of experience in leading engineering/applied research/ML experiences in natural language processing, SOTA generative AI models
Proven record of consistent delivery of technology/products across the full Machine Learning life cycle
MS or Ph.D. in Computer Science, Machine Learning, information retrieval, data mining, or a related field

Preferred

Strong background and experience in Machine Learning, NLP, and RAG.
Strong engineering and R&D experience in LLM post-training, advanced RL-based methods to improve LLM models' safety and quality using RLHF/RLAIF, reward model, advanced RL policy optimization algorithms, cutting-edge hallucination reduction methods, and their engineering implementation, hands-on experience to develop and ship RL based models with high availability, low latency, robustness, and stability.
Exceptional verbal and written communication skills to lead
Excellent product vision and sound business acumen. Ability to manage long-term strategy and short-term deliverables.
Strong engineering leadership and fundamentals.

Responsibilities

Apple is where individual imaginations gather together, contributing to the values that lead to great work. Every The AI, Search & Knowledge Platforms team builds amazing products and services for Apple's customers while serving as a foundational partner to teams across Apple. The team delivers world-class AI, search, and knowledge systems powering Siri, Apple Intelligence, Safari, and iMessage, and operates the foundational platforms and infrastructure that keep these intelligent experiences running at hyperscale.
You will lead the strong team of MLE, SWE, and data engineers responsible for delivering efficient and effective Generative AI models to build and improve the summarization capabilities across different data types.
In this role, you'll drive E2E R&D and engineering to generate high-quality summaries and experiences for Apple users. This includes on-device LLM models for personal content summarization across 1P and 3P apps, and powerful summarization models on Apple's Private Cloud Compute servers. In addition, improve the summarization models' quality for world knowledge-seeking questions and Safari pages to provide accurate answers and highlight web page gists in real-time. Lead the team to develop SOTA LLM-based generative models, groundedness models, and safety models for accurate, grounded, concise, and safe summaries. Develop sophisticated on-device and on-server software frameworks for context integration fast and cost-efficient LLM-based model inference. Integrate the Apple ecosystem with Apple's LLM infrastructure and generative models to deliver delightful user experiences. Devise the product vision and strategy and execute the plan to deliver the highest quality end-user experience. Collaborate with various organizational partners to profoundly impact billions of Apple users worldwide.

View full posting on CareerOneStop → ID: 01ef76150873

Senior ML Engineer

Uber · Seattle, WA

Senior

2026-05-13

WA 2026-05-13

Preferred

--- What the Candidate Will Do ----
Translate business and security needs into well-defined ML problems.
Develop, iterate, and productionize ML models that drive risk-adaptive decisions in real-time.
Engineer features from Uber's risk systems, logs, and contextual signals.
Integrate ML systems into Uber's critical access pathways (containers, APIs, gateways, data).
Collaborate across Security, Risk, and Infra teams to deliver scalable, production-ready solutions.
Provide leadership by mentoring junior engineers, evangelize ML best practices, and help shape ML strategy within AI Security.
--- Basic Qualifications ----
5+ years experience in formulating ML problems from ambiguous business requirements, especially in risk, fraud, or security contexts.
Proficiency across a broad range of ML algorithms: tree-based models (XGBoost, LightGBM), classical statistical models (logistic regression, SVMs), and deep learning architectures (CNNs, RNNs, Transformers), with the ability to select and apply the right approach based on context and data characteristics.
Hands-on experience with feature engineering, model development, and productionization of ML pipelines.
Proficiency in PyTorch, TensorFlow, or similar ML frameworks, and in Python or comparable languages for scalable, production-grade systems.
--- Preferred Qualifications ----
Proven ability to own ML systems end-to-end: from requirement discovery ? feature design ? modeling ? deployment.
Deep experience with advanced ML techniques, including ensemble methods, neural networks, graph-based models, and handling challenges like imbalanced data, feedback loops, and iterative retraining.
Familiarity with large-scale data/infra systems (Kafka, Pinot, Hive, Cassandra, Spark, Flink).
Background in access control, authentication, or enterprise security systems.
Track record of technical leadership: mentoring engineers, driving cross-functional initiatives, or shaping ML/security strategy.
For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Responsibilities

Uber's newly formed AI Security team, part of the Core Security Engineering organization, is building the foundation for dynamic, data-driven security systems. We're evolving Uber's Zero Trust Architecture (ZTA) to be more risk-adaptive across authentication and authorization, moving beyond static rules and manual approvals toward real-time, ML-driven access decisions that secure both humans and AI agents without slowing them down.
As a Senior ML Engineer, you'll translate ambiguous business and security needs into concrete ML problems, design and iterate on solutions, and take them end-to-end into production. This is greenfield work at the intersection of ML, security, and infrastructure, shaping how Uber secures AI at scale.

View full posting on CareerOneStop → ID: 4e4b18c58011

Sr Machine Learning Engineer, Pricing

Uber · Seattle, WA

Senior Doctorate

2026-05-13

WA 2026-05-13

Requirements

Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
4+ years of experience in developing and deploying machine learning models and optimization algorithms in large-scale production environments, delivering measurable business impact over multiple quarters and making significant technical contributions
Proficiency in programming languages such as Python, Scala, Java, or Go
Experience with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
Experience in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. LP, convex optimization)

Preferred

Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavio
Experience leading complex technical projects and influencing the scope and output of others
Track record of translating ambiguous business problems into technical solutions and driving multi-functional projects
Excellent communication skills to lead initiatives and collaborate effectively with cross-functional partners
Experience in reinforcement learning and causal machine learning
For New York, NY-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Responsibilities

Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders.
We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.
*What You Will Do
Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips
Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
Collaborate with the team leads to set the team's technical direction and own its implementation, providing technical mentorship to junior engineers
Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

View full posting on CareerOneStop → ID: 618f44deac05

Staff Machine Learning Engineer - Marketplace Pricing

Uber · Seattle, WA

Senior Doctorate

2026-05-13

WA 2026-05-13

Requirements

Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters
Proficiency in programming languages such as Python, Scala, Java, or Go
Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavio
Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization)

Preferred

Experience developing multi-year technical strategies and cross-team platform architecture, and proficiency owning technical roadmap and leading complex technical projects while substantially influencing the scope and output of others
Track record of translating complex business problems into technical solutions and driving multi-functional projects across multiple teams
Excellent communication skills to lead initiatives across multiple product areas and collaborate effectively with cross-functional teams
Proficiency in reinforcement learning and causal machine learning
For New York, NY-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Responsibilities

Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders.
We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.
*What You Will Do
Drive technical strategy and roadmap ownership over a 1+ year horizon and own the implementation, including platform-level architecture decisions, executive communication and alignment, technical mentorship, and cross-team technical influence
Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips
Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

View full posting on CareerOneStop → ID: 012994d721c5

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Olympia, WA

Director Doctorate

2026-05-13

WA 2026-05-13

Requirements

Director, Data Science - AI for Work (AI4W) Ecosystem Responsibilities:
Collaborate with Engineering, Product, and cross-functional teams to inform, influence, support, and execute strategy and investment decisions for Meta.
Contribute to the long-term technical vision and strategy for analytics methods and metrics to enhance the quality and efficiency of our platforms at scale.
Work with engineering and other data scientists to build and improve AI development, automation, experimentation, and measurement methods and metrics, ensuring high-quality throughput and impact.
Develop an understanding of complex, large-scale AI development, experimentation, and measurement systems, as well as broader industry challenges, to identify current and future risks and opportunities.
Inspire, and lead a team of data scientists and managers across multiple teams in close collaboration with other Data Science Directors and Managers.
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
10+ years of work experience leading analytics work in IC capacity, working collaboratively with Engineering and cross-functional partners, and guiding data-influenced product planning, prioritization and strategy development
Experience working effectively with multiple stakeholders and cross-functional teams, including Engineering, PM/TPM, Analytics and Finance
Experience framing and communication skills

Preferred

Masters or Ph.D. Degree in a quantitative field
Experience with predictive modeling, machine learning, and experimentation/causal inference methods
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Responsibilities

AI for Work (AI4W) is Meta's company-wide effort to integrate AI into every tool, team, and process at Meta. This role will be the founding senior IC on a new "AI4W Ecosystem" analytics team.We are seeking a Data Science Director (IC) who is passionate about developing, measuring, and strategizing investments of Meta's products. As a Data Scientist, you will collaborate with cross-functional partners to identify and solve complex problems using data and analysis. Your role will involve shaping product development, quantifying new opportunities, and ensuring products bring value to users and the company. You will guide teams using data-driven insights, develop hypotheses, and employ rigorous analytical approaches to test them. You will tell data-driven stories, present clear insights, and build credibility with stakeholders. By joining our team, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.

View full posting on CareerOneStop → ID: 78590a86e3e2

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Olympia, WA

Director Doctorate

2026-05-13

WA 2026-05-13

Requirements

Director, Data Science - AI for Work (AI4W) Ecosystem Responsibilities:
Collaborate with Engineering, Product, and cross-functional teams to inform, influence, support, and execute strategy and investment decisions for Meta.
Contribute to the long-term technical vision and strategy for analytics methods and metrics to enhance the quality and efficiency of our platforms at scale.
Work with engineering and other data scientists to build and improve AI development, automation, experimentation, and measurement methods and metrics, ensuring high-quality throughput and impact.
Develop an understanding of complex, large-scale AI development, experimentation, and measurement systems, as well as broader industry challenges, to identify current and future risks and opportunities.
Inspire, and lead a team of data scientists and managers across multiple teams in close collaboration with other Data Science Directors and Managers.
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
10+ years of work experience leading analytics work in IC capacity, working collaboratively with Engineering and cross-functional partners, and guiding data-influenced product planning, prioritization and strategy development
Experience working effectively with multiple stakeholders and cross-functional teams, including Engineering, PM/TPM, Analytics and Finance
Experience framing and communication skills

Preferred

Masters or Ph.D. Degree in a quantitative field
Experience with predictive modeling, machine learning, and experimentation/causal inference methods
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Responsibilities

AI for Work (AI4W) is Meta's company-wide effort to integrate AI into every tool, team, and process at Meta. This role will be the founding senior IC on a new "AI4W Ecosystem" analytics team.We are seeking a Data Science Director (IC) who is passionate about developing, measuring, and strategizing investments of Meta's products. As a Data Scientist, you will collaborate with cross-functional partners to identify and solve complex problems using data and analysis. Your role will involve shaping product development, quantifying new opportunities, and ensuring products bring value to users and the company. You will guide teams using data-driven insights, develop hypotheses, and employ rigorous analytical approaches to test them. You will tell data-driven stories, present clear insights, and build credibility with stakeholders. By joining our team, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.

View full posting on CareerOneStop → ID: 5466a2cf6504

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Boise, ID

Director

2026-05-13

ID 2026-05-13

View full posting on CareerOneStop → ID: 85d207c38bdb

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Salem, OR

Director

2026-05-13

OR 2026-05-13

View full posting on CareerOneStop → ID: 666484586807

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Salem, OR

Director

2026-05-13

OR 2026-05-13

View full posting on CareerOneStop → ID: 547b2bd3115a

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Helena, MT

Director

2026-05-13

MT 2026-05-13

View full posting on CareerOneStop → ID: b5856f1a685a

AIML - Sr Machine Learning Engineer, Data and ML Innovation

Apple · Sunnyvale, CA

Senior

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 6b34f8fc85a5

Applied ML Engineer

Paramount · Los Angeles, CA

Mid-level

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: c7cc828cb229

Artificial Intelligence / Machine Learning - Intern

Bosch · Sunnyvale, CA

Intern

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 130a3b096d24

Data Science Intern - Model Optimization

quadric.io, Inc · Burlingame, CA

Intern

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: a2b46430792c

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Cheyenne, WY

Director

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 59e234916d06

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Salt Lake City, UT

Director

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: f53ce2f47f59

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Pierre, SD

Director

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: f101009e3aef

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Bismarck, ND

Director

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 35cff1563019

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Carson City, NV

Director

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: a6a7f0418587

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Carson City, NV

Director

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 35a0d95c1787

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Denver, CO

Director

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 807fefa56950

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Pierre, SD

Director

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 0340a4c97432

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Sacramento, CA

Director

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: a822000db3b3

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Cheyenne, WY

Director

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: a5e44831a4ab

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Salt Lake City, UT

Director

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 51bfe3fc12e6

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Bismarck, ND

Director

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 56b214e60b04

Machine Learning Engineer - Health AIML

Apple · Cupertino, CA

Mid-level

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 51d5516404f4

Machine Learning Engineer II

Uber · Sunnyvale, CA

Mid-level

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 6446de86e86f

Machine Learning Engineer II

Uber · San Francisco, CA

Mid-level

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 4ce93513e961

Machine Learning Engineer II, Pricing

Uber · San Francisco, CA

Mid-level

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 442bb6ccad18

Machine Learning Engineer II, Pricing

Uber · Sunnyvale, CA

Mid-level

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: abaa0f16b962

Machine Learning Engineer/Senior Machine Learning Engineer - Infra

Genentech · South San Francisco, CA

Senior

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 4c04d143dc1f

Senior Machine Learning Manager, Search & Knowledge Platform

Apple · Santa Clara, CA

Manager

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: c39885d38bac

Senior ML Engineer

Uber · San Francisco, CA

Senior

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: bd828cdb2db1

Sr Machine Learning Engineer, Pricing

Uber · Sunnyvale, CA

Senior

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 364f60b57a94

Sr Machine Learning Engineer, Pricing

Uber · San Francisco, CA

Senior

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 88466dd62232

Staff Machine Learning Engineer - Marketplace Pricing

Uber · Sunnyvale, CA

Senior

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 9c245d2156ad

Staff Machine Learning Engineer - Marketplace Pricing

Uber · San Francisco, CA

Senior

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 5d4bab5c635f

Data Scientist - INTL India - 99c1e7e0

Insight Global · Tempe, AZ

Mid-level

2026-05-13

AZ 2026-05-13

View full posting on CareerOneStop → ID: 4ded0839ae54

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Phoenix, AZ

Director

2026-05-13

AZ 2026-05-13

View full posting on CareerOneStop → ID: ec58b913fedb

Sr. Manager , Annapurna Labs - Cloud Scale Machine Learning Acceleration Team

Amazon · Tempe, AZ

Manager

2026-05-13

AZ 2026-05-13

View full posting on CareerOneStop → ID: 5c0c1505aed5

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Santa Fe, NM

Director

2026-05-13

NM 2026-05-13

View full posting on CareerOneStop → ID: 891146a46105

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Santa Fe, NM

Director

2026-05-13

NM 2026-05-13

View full posting on CareerOneStop → ID: 8ee7c16731cf

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Lincoln, NE

Director

2026-05-13

NE 2026-05-13

View full posting on CareerOneStop → ID: 2c09f0a2bb98

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Lincoln, NE

Director

2026-05-13

NE 2026-05-13

View full posting on CareerOneStop → ID: df0b5334387f

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Topeka, KS

Director

2026-05-13

KS 2026-05-13

View full posting on CareerOneStop → ID: e5e92dd4df81

Data Scientist

Love's Travel Stops & Country Stores · Oklahoma City, OK

Mid-level

2026-05-13

OK 2026-05-13

View full posting on CareerOneStop → ID: a0ed38aa9f84

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Oklahoma City, OK

Director

2026-05-13

OK 2026-05-13

View full posting on CareerOneStop → ID: 66aeebe84928

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Oklahoma City, OK

Director

2026-05-13

OK 2026-05-13

View full posting on CareerOneStop → ID: fdeaf931bcf8

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Austin, TX

Director

2026-05-13

TX 2026-05-13

View full posting on CareerOneStop → ID: 6ac036a62eb0

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Austin, TX

Director

2026-05-13

TX 2026-05-13

View full posting on CareerOneStop → ID: 4fa1cb0dfcf4

Senior Specialist - Data Science - Fraud Analytics

Ally · Austin, TX

Senior

2026-05-13

TX 2026-05-13

View full posting on CareerOneStop → ID: 3a6d4eeba527

Statistician/Data Scientist - Data Insights and Decision Support

General Motors · Austin, TX

Mid-level

2026-05-13

TX 2026-05-13

View full posting on CareerOneStop → ID: 14107aa16331

Data Scientist III

RELX INC · Minneapolis, MN

Mid-level

2026-05-13

MN 2026-05-13

View full posting on CareerOneStop → ID: fcb67947d859

Data Scientist III

RELX INC · Saint Paul, MN

Mid-level

2026-05-13

MN 2026-05-13

View full posting on CareerOneStop → ID: f34990984678

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Saint Paul, MN

Director

2026-05-13

MN 2026-05-13

View full posting on CareerOneStop → ID: 8b35ed1f05eb

Grad Degree Intern (GIH Research - Data Science)

Mayo Clinic · Rochester, MN

Intern

2026-05-13

MN 2026-05-13

View full posting on CareerOneStop → ID: 32b2e244a7e5

Manager & Senior Data Scientist

Travelers Insurance Company · Saint Paul, MN

Manager

2026-05-13

MN 2026-05-13

View full posting on CareerOneStop → ID: 859a493979c3

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Des Moines, IA

Director

2026-05-13

IA 2026-05-13

View full posting on CareerOneStop → ID: e366d88a1034

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Jefferson City, MO

Director

2026-05-13

MO 2026-05-13

View full posting on CareerOneStop → ID: 9957af6fab14

Data Scientist (MMM)

FocusKPI Inc. · Bentonville, AR

Mid-level

2026-05-13

AR 2026-05-13

View full posting on CareerOneStop → ID: 3462518d1941

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Little Rock, AR

Director

2026-05-13

AR 2026-05-13

View full posting on CareerOneStop → ID: 7d531596dd0a

Principal, Data Scientist

Walmart · Bentonville, AR

Senior

2026-05-13

AR 2026-05-13

View full posting on CareerOneStop → ID: 51638ca55141

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Baton Rouge, LA

Director

2026-05-13

LA 2026-05-13

View full posting on CareerOneStop → ID: eb5c8ab0d09e

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Madison, WI

Director

2026-05-13

WI 2026-05-13

View full posting on CareerOneStop → ID: babab41d4932

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Madison, WI

Director

2026-05-13

WI 2026-05-13

View full posting on CareerOneStop → ID: 2c155de6a944

Staff Machine Learning Engineer, AI Rese

CRIBL INC · Madison, WI

Senior

2026-05-13

WI 2026-05-13

View full posting on CareerOneStop → ID: 68eb17684404

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Springfield, IL

Director

2026-05-13

IL 2026-05-13

View full posting on CareerOneStop → ID: f1da104817fc

Machine Learning Intern, Fall 2026 (Internship) - 4 months

BMO Financial Group · Chicago, IL

Intern

2026-05-13

IL 2026-05-13

View full posting on CareerOneStop → ID: 30d62e99a93c

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Jackson, MS

Director

2026-05-13

MS 2026-05-13

View full posting on CareerOneStop → ID: eb23276414be

Data Scientist

SAIC · Huntsville, AL

Mid-level

2026-05-13

AL 2026-05-13

View full posting on CareerOneStop → ID: 2f30bf7fcbe0

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Montgomery, AL

Director

2026-05-13

AL 2026-05-13

View full posting on CareerOneStop → ID: 8359e2e39d93

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Nashville, TN

Director

2026-05-13

TN 2026-05-13

View full posting on CareerOneStop → ID: 642b7134383a

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Nashville, TN

Director

2026-05-13

TN 2026-05-13

View full posting on CareerOneStop → ID: 0c9f3386b3fd

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Frankfort, KY

Director

2026-05-13

KY 2026-05-13

View full posting on CareerOneStop → ID: b2ee8e3a94a2

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Atlanta, GA

Director

2026-05-13

GA 2026-05-13

View full posting on CareerOneStop → ID: 0f3dc71d026c

Senior Data Scientist

Fiserv · Alpharetta, GA

Senior

2026-05-13

GA 2026-05-13

View full posting on CareerOneStop → ID: 8bcab11fc9a2

Data Scientist II - Fraud Reporting

Truist · Charlotte, NC

Mid-level

2026-05-13

NC 2026-05-13

View full posting on CareerOneStop → ID: a0203ef47865

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Raleigh, NC

Director

2026-05-13

NC 2026-05-13

View full posting on CareerOneStop → ID: 4d178f2119a0

Director, Data Science - AI for Work (AI4W) Ecosystem

Meta · Raleigh, NC

Director

2026-05-13

NC 2026-05-13

View full posting on CareerOneStop → ID: a0591b8af2bc

AI/ML Engineer - Vice President (Seattle, WA)

Goldman Sachs · Seattle, WA

Director

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 8424c149c513

Data Scientist II

F5, Inc. · Seattle, WA

Mid-level

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: fdcd8c81601b

Senior Data Scientist

Adobe Inc. · Seattle, WA

Senior

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: c060290bdafe

Staff Machine Learning Engineer, AI Research

Cribl, Inc · Olympia, WA

Senior

2026-05-13

WA 2026-05-13

View full posting on CareerOneStop → ID: 04b650759ea3

Senior Data Scientist, Special Projects

Amazon · Seattle, WA

Senior Doctorate

2026-05-12

WA 2026-05-12

Requirements

5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
4+ years of data scientist experience
Experience with statistical models e.g. multinomial logistic regression
MS or PhD in Statistics, Biostatistics, Data Science, or related quantitative field
5+ years of experience applying statistical methods to healthcare data
Experience with statistical modeling and analysis of longitudinal data
Advance in experimental design and hypothesis testing

Preferred

2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
Experience managing data pipelines
Experience as a leader and mentor on a data science team
PhD in Statistics, Biostatistics, Data Science, or related quantitative field
Experience analyzing healthcare data
Knowledge of healthcare industry regulations and processes
Familiarity with healthcare data standards
Experience applying causal inference frameworks to real-world problems
Familiarity with modern causal discovery and inference techniques
Knowledge of counterfactual analysis methods

Responsibilities

In this role, you will:
Analyze complex healthcare data to identify patterns, trends, and insights
Develop and validate statistical methodologies
Create and maintain analytical frameworks
Provide recommendations on data collection strategies
Collaborate with Applied Scientists to support model development efforts
Design and implement statistical analyses to validate analytical approaches
Present findings to stakeholders and contribute to scientific publications
Work with cross-functional teams to ensure solutions are built on sound statistical foundations
Design and implement causal inference analyses to understand underlying mechanisms
Develop frameworks for identifying and validating causal relationships in complex systems
Work with stakeholders to translate causal insights into actionable recommendations
You'll work with large-scale healthcare datasets, conducting sophisticated statistical analyses to generate actionable insights. You'll collaborate with Applied Scientists to validate model predictions and ensure statistical rigor in our approach. Regular interaction with product teams will help translate analytical findings into practical improvements for our services.

View full posting on CareerOneStop → ID: 59eba2a6d93b

Senior Data Scientist

Nelnet · Olympia, WA

Senior Doctorate

2026-05-12

WA 2026-05-12

Requirements

2+ years of experience in data analysis.
1+ years of programming experience.
Significant experience working with large, complex data sets and common data science tools.
Experience working with database Python.
Experience designing, building, deploying, and validating machine-learning predictive models, ideally within a business framework.
Experience training multi model design to structure and train for unstructured data matching.
Experience training LLM models for specialized use cases
*COMPETENCIES - SKILLS/KNOWLEDGE/ABILITIES:
Highly inquisitive and self-motivated.
Ability to map out solutions with a starting point and end goal, but with few steps identified in-between.
Exceptional ability to analyze and synthesize data.
Advanced proficiency in SQL and Python.
Competency navigating and working within the AWS cloud suite.
Competency designing self-learning models that result in logarithm trends to identify trends in data to predict potential outcomes or missing data fields.
Core understanding of statistical concepts and methods.
Competency in the MS Office Suite.
Highly accountable and inquisitive, able to manage multiple tasks in a fast-paced, dynamic environment.
Self-motivated.
Excellent communication skills (written, verbal, and interpersonal) to coordinate across teams and deliver polished presentations.
Experience with training NumPy and Pandas models.

Education

PHD degree required in a Quantitative (heavy in mathematics, statistics or analysis, such as Applied Mathematics, Optimization, Psychology, or Economics) or Programming discipline.

Responsibilities

Conduct advanced analyses and statistical deep dives, with a focus on producing actionable recommendations and strategic guidance for decision makers.
Develop and deploy custom models and algorithms using data and machine learning libraries to solve complex business problems.
Mine, clean, process, transform and join data from a variety of sources including SQL servers, AWS environments, Azure, SnowFlake, SalesForce, internal systems, and flat files.
Identify, wrangle, scrape, and assemble new data sources from the web, data aggregators, and public sources.
Build rich, interactive dashboards and visualizations from the ground up using PowerBI.
Compile and present key findings and reports to all levels of the organization, including senior leadership.
Continuously seek out opportunities to add value through process automation and programmatic solutions to manual tasks and monitor and improve Data Science model performance.
Act as a subject matter expert within the data science field. Continuously learn, grow, and explore new emerging technologies. (Stay up to date with industry trends and best practices.
Problem-solve, generate new ideas, and provide creative solutions.
Mentor, model, act as a resource, and provide guidance for more junior analysts and team members.
Lead development, testing and implementation of machine-learning models and algorithms using data and machine learning to solve complex business problems.

View full posting on CareerOneStop → ID: 148da44b0a7b

Data Scientist/Statistician

Intel · Hillsboro, OR

Mid-level Doctorate

2026-05-12

WA 2026-05-12

Requirements

You must possess the minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
Master's or PhD degree in Statistics, Data Science or Industrial Engineering.
4+ years working in statistics or data science
2+ years working on quality systems such as process control systems and change control systems
1+ year working on PowerBI or similar dashboards
1+ years in data analytics and machine learning (Python, R, JMP, etc.) and relational databases (SQL).

Preferred

1+ years working on fault detection systems
2+ years in a Technical leadership role.
3+ months working knowledge with any of following technologies: JSL, Python, Spark, NiFi, Hadoop, HBase, S3 object storage, Kubernetes, REST APIs and services.
3+ months working knowledge with CI/CD (Continuous Integration/Continuous Deployment) and proficiency with GitHub and GitHub Actions.
Prior interaction with factory automation systems
Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.

Responsibilities

Intel Foundry Statistics and Data Science team's mission is to drive statistically sound methodologies into business practices and systems to help organization manage change control decisions, monitor capability of the process, ensure matching across tools and fabs, and drive best in class process control systems. Our team reports into the foundry quality and reliability team and is essential for driving transformation of Intel to be focused on not just process development, but a great partner for our foundry customers to help turn data into information. Our team is looking for an engineer with background in statistics and data science with strong technical skills in applied statistics, good communication skills, ability to also help support and develop modern AI/ML solutions.
As a Statistician and Data Scientist in the TD AI office, you will partner with Intel's factory automation organization and Foundry TD's functional areas to support semiconductor process development and transfer of these systems to worldwide virtual factory network.
The primary responsibilities for this role will include, but are not limited to:
Ensuring organization leverages appropriate data and analyses to make change control decisions
Drives organization to use process control systems to improve capability, matching, and stability of semiconductor process technologies
Use predictive modeling, statistics, Machine Learning, Data Mining, and other data analysis techniques to collect, explore, and extract insights from the structure and unstructured data.
Develop software, algorithms and applications to apply mathematics to data, perform large scale experimentation and build data driven apps to translate data into intelligence, solve a variety of business problems and enable business strategy.
Assist the business with casual inferences; observations with finding patterns and relationships in data.
Interfacing with process and integration functional area analytics teams to help solve problems
A successful candidate will have proven experience demonstrating the following skills and behavioral traits:
Experience in using AI/ML/Analytics algorithms and methodologies
Developing statistical methodologies
Ability to code statistical analysis, data cleaning, and data manipulation via common languages such as JSL, Python, and SQL
Understanding of data structures
Strong written and oral communication skills.
Ability to train others
Analytical problem solving and troubleshooting skills.
Teamwork skills and partnership skills.
High tolerance of ambiguity.
High level of self-motivation

View full posting on CareerOneStop → ID: 8ef4c4eed089

Senior Data Scientist

Nelnet · Boise, ID

Senior

2026-05-12

ID 2026-05-12

View full posting on CareerOneStop → ID: aa3b6bacd48a

Senior Data Scientist

Nelnet · Salem, OR

Senior

2026-05-12

OR 2026-05-12

View full posting on CareerOneStop → ID: 627ec4491e49

Senior Data Scientist

Nelnet · Helena, MT

Senior

2026-05-12

MT 2026-05-12

View full posting on CareerOneStop → ID: edf40392b668

(USA) Staff, Data Scientist

Walmart · Sunnyvale, CA

Senior

2026-05-12

WA 2026-05-12

View full posting on CareerOneStop → ID: 7ee6d00a12a6

AI/ML Engineer (Hybrid)

Cisco · San Jose, CA

Mid-level

2026-05-12

WA 2026-05-12

View full posting on CareerOneStop → ID: 15100ec5664b

Camera Machine Learning Engineer - Camera Hardware

Apple · San Francisco, CA

Mid-level

2026-05-12

WA 2026-05-12

View full posting on CareerOneStop → ID: 195019923c17

Senior Data Scientist

Nelnet · Cheyenne, WY

Senior

2026-05-12

WY 2026-05-12

View full posting on CareerOneStop → ID: 5ec85a0d5c6d

Senior Data Scientist

Nelnet · Draper, UT

Senior

2026-05-12

UT 2026-05-12

View full posting on CareerOneStop → ID: 7866bcde42a5

Senior Data Scientist

Nelnet · Salt Lake City, UT

Senior

2026-05-12

UT 2026-05-12

View full posting on CareerOneStop → ID: 8915d4b5c064

Summer Undergrad Data Science Intern

University of Utah · Salt Lake City, UT

Intern

2026-05-12

UT 2026-05-12

View full posting on CareerOneStop → ID: 52dab13279d5

Senior Data Scientist

Nelnet · Carson City, NV

Senior

2026-05-12

NV 2026-05-12

View full posting on CareerOneStop → ID: b6da091cd465

Senior Data Scientist

Nelnet · Bismarck, ND

Senior

2026-05-12

ND 2026-05-12

View full posting on CareerOneStop → ID: 52cca700467c

Senior Data Scientist

Nelnet · Aberdeen, SD

Senior

2026-05-12

SD 2026-05-12

View full posting on CareerOneStop → ID: 5eb571473332

Senior Data Scientist

Nelnet · Sioux Falls, SD

Senior

2026-05-12

SD 2026-05-12

View full posting on CareerOneStop → ID: 82287a557f8b

Senior Data Scientist

Nelnet · Pierre, SD

Senior

2026-05-12

SD 2026-05-12

View full posting on CareerOneStop → ID: f60efbc8182b

Machine Learning Engineer

SAP · Palo Alto, CA

Mid-level

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: bbddf971feee

Photonic Engineer, Machine Learning Systems, Platforms

Google · Sunnyvale, CA

Mid-level

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: 01485d4f393e

Principal Machine Learning Engineer

Palo Alto Networks · Santa Clara, CA

Senior

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: e32748c6329a

Product Data Scientist, Insights, Analytics, Platforms and Devices

Google · Mountain View, CA

Mid-level

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: 5fc1c648a787

Senior Data Scientist

Nelnet · Sacramento, CA

Senior

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: ed4a527e20e2

Senior Developer Relations Manager - Data Processing and Data Science

NVIDIA · Santa Clara, CA

Manager

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: 9aaec6da048b

Senior Machine Learning Engineer - Physical AI and Synthetic Data Generation

NVIDIA · Santa Clara, CA

Senior

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: 43c44b787df7

Senior Research Data Scientist, Core Safety Data Science

Google · Mountain View, CA

Senior

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: 251ccbc9dfae

Senior Scientist, Agentic AI and Machine Learning (PDMB)

Merck · South San Francisco, CA

Senior

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: 2b2356bd3b27

Software Engineer, Machine Learning

Google · Mountain View, CA

Mid-level

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: 289b04d02b5a

Software Engineer, Machine Learning Platform (Tapestry)

Google · Mountain View, CA

Mid-level

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: 49ba8d652772

Sr Data Scientist - Global Supply Chain and Logistics

Target · Sunnyvale, CA

Senior

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: 8e6b496c3b33

Sr. Machine Learning Engineer, ASR Infrastructure and Tools, Siri Speech

Apple · Cupertino, CA

Senior

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: da36e0d20ed2

Sr. Machine Learning Scientist, Siri Speech

Apple · Cupertino, CA

Senior

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: bb6d82975978

Data Scientist/Sr Data Scientist, IT Analytics

American Airlines · Phoenix, AZ

Senior

2026-05-12

AZ 2026-05-12

View full posting on CareerOneStop → ID: 7c13b75c629e

Data Scientist/Statistician

Intel · Phoenix, AZ

Mid-level

2026-05-12

AZ 2026-05-12

View full posting on CareerOneStop → ID: eb9bf3fa68e5

Senior Data Scientist

Nelnet · Phoenix, AZ

Senior

2026-05-12

AZ 2026-05-12

View full posting on CareerOneStop → ID: 2bdfe2210e51

Senior Data Scientist

Nelnet · Santa Fe, NM

Senior

2026-05-12

NM 2026-05-12

View full posting on CareerOneStop → ID: 2e3109ca2f8c

Senior Data Scientist

Nelnet · Aurora, CO

Senior

2026-05-12

CO 2026-05-12

View full posting on CareerOneStop → ID: 667c03b7a5ee

Senior Data Scientist

Nelnet · Fort Morgan, CO

Senior

2026-05-12

CO 2026-05-12

View full posting on CareerOneStop → ID: 6a5aca1c0fa5

Senior Data Scientist

Nelnet · Breckenridge, CO

Senior

2026-05-12

CO 2026-05-12

View full posting on CareerOneStop → ID: 21a81476539a

Senior Data Scientist

Nelnet · Highlands Ranch, CO

Senior

2026-05-12

CO 2026-05-12

View full posting on CareerOneStop → ID: 5235825f05e1

Senior Data Scientist

Nelnet · Denver, CO

Senior

2026-05-12

CO 2026-05-12

View full posting on CareerOneStop → ID: 713a6ea75e4f

Senior Data Scientist

Nelnet · Ogallala, NE

Senior

2026-05-12

NE 2026-05-12

View full posting on CareerOneStop → ID: 5edb50ac0579

Senior Data Scientist

Nelnet · Columbus, NE

Senior

2026-05-12

NE 2026-05-12

View full posting on CareerOneStop → ID: 7b121645323b

Senior Data Scientist

Nelnet · Lincoln, NE

Senior

2026-05-12

NE 2026-05-12

View full posting on CareerOneStop → ID: 8dfa25cb8875

Senior Data Scientist

Nelnet · North Platte, NE

Senior

2026-05-12

NE 2026-05-12

View full posting on CareerOneStop → ID: c943ce937f8d

Senior Data Scientist

Nelnet · Imperial, NE

Senior

2026-05-12

NE 2026-05-12

View full posting on CareerOneStop → ID: 08a9622687b7

Senior Data Scientist

Nelnet · Bellevue, NE

Senior

2026-05-12

NE 2026-05-12

View full posting on CareerOneStop → ID: 30609229d0c8

Senior Data Scientist

Nelnet · Gering, NE

Senior

2026-05-12

NE 2026-05-12

View full posting on CareerOneStop → ID: 686fb44d065b

Senior Data Scientist

Nelnet · Scottsbluff, NE

Senior

2026-05-12

NE 2026-05-12

View full posting on CareerOneStop → ID: 6bff1431837b

Senior Data Scientist

Nelnet · Sidney, NE

Senior

2026-05-12

NE 2026-05-12

View full posting on CareerOneStop → ID: 85341dd091ee

Senior Data Scientist

Nelnet · Alliance, NE

Senior

2026-05-12

NE 2026-05-12

View full posting on CareerOneStop → ID: d1f545b42e9f

Senior Data Scientist

Nelnet · Hastings, NE

Senior

2026-05-12

NE 2026-05-12

View full posting on CareerOneStop → ID: 0894d47eb56a

Senior Data Scientist

Nelnet · Omaha, NE

Senior

2026-05-12

NE 2026-05-12

View full posting on CareerOneStop → ID: 6dacec3eaf78

Senior Data Scientist

Nelnet · Topeka, KS

Senior

2026-05-12

KS 2026-05-12

View full posting on CareerOneStop → ID: 745ea0e1bb5c

Senior Data Scientist

Nelnet · Oklahoma City, OK

Senior

2026-05-12

OK 2026-05-12

View full posting on CareerOneStop → ID: 90f989334352

Senior Data Scientist

Nelnet · Austin, TX

Senior

2026-05-12

TX 2026-05-12

View full posting on CareerOneStop → ID: 0a022d0915ac

Senior Data Scientist

Nelnet · Burleson, TX

Senior

2026-05-12

TX 2026-05-12

View full posting on CareerOneStop → ID: 81f61c2af5d3

Systems Engineering Intern - Machine Learning

Texas Instruments · Dallas, TX

Intern

2026-05-12

TX 2026-05-12

View full posting on CareerOneStop → ID: 9adfee8292fd

Senior Data Scientist

Nelnet · Eagan, MN

Senior

2026-05-12

MN 2026-05-12

View full posting on CareerOneStop → ID: e4f6c552a5fd

Senior Data Scientist

Nelnet · Saint Paul, MN

Senior

2026-05-12

MN 2026-05-12

View full posting on CareerOneStop → ID: e338577690b2

Senior Data Scientist

Nelnet · Des Moines, IA

Senior

2026-05-12

IA 2026-05-12

View full posting on CareerOneStop → ID: 24d82f500285

Senior Data Scientist

Nelnet · Jefferson City, MO

Senior

2026-05-12

MO 2026-05-12

View full posting on CareerOneStop → ID: 607053b04bb6

Data Scientist

Uniti · Little Rock, AR

Mid-level

2026-05-12

AR 2026-05-12

View full posting on CareerOneStop → ID: 6a27e6a97290

Senior Data Scientist

Nelnet · Little Rock, AR

Senior

2026-05-12

AR 2026-05-12

View full posting on CareerOneStop → ID: 2c935e9b47d4

Staff, Data Scientist

Walmart · Bentonville, AR

Senior

2026-05-12

AR 2026-05-12

View full posting on CareerOneStop → ID: 3798bad345a9

Senior Data Scientist

Nelnet · Baton Rouge, LA

Senior

2026-05-12

LA 2026-05-12

View full posting on CareerOneStop → ID: 0dd6c25aaf59

Senior Data Scientist

Nelnet · Boscobel, WI

Senior

2026-05-12

WI 2026-05-12

View full posting on CareerOneStop → ID: 14d9df42ee81

Senior Data Scientist

Nelnet · Stevens Point, WI

Senior

2026-05-12

WI 2026-05-12

View full posting on CareerOneStop → ID: f19c8f5c1b36

Senior Data Scientist

Nelnet · Eau Claire, WI

Senior

2026-05-12

WI 2026-05-12

View full posting on CareerOneStop → ID: 3fb7d639e707

Senior Data Scientist

Nelnet · Madison, WI

Senior

2026-05-12

WI 2026-05-12

View full posting on CareerOneStop → ID: cd83de4ea46b

Senior Data Scientist

Nelnet · Springfield, IL

Senior

2026-05-12

IL 2026-05-12

View full posting on CareerOneStop → ID: 4adb6332c43c

Senior Data Scientist

Nelnet · Jackson, MS

Senior

2026-05-12

MS 2026-05-12

View full posting on CareerOneStop → ID: 9b63b4aab712

Staff Machine Learning Engineer, AI Research

Cribl, Inc · Clarksdale, MS

Senior

2026-05-12

MS 2026-05-12

View full posting on CareerOneStop → ID: 4b24efa12e5c

Senior Data Scientist

Nelnet · Montgomery, AL

Senior

2026-05-12

AL 2026-05-12

View full posting on CareerOneStop → ID: f33b1abe89fe

Data Scientist- #26-10985

US Tech Solutions · Chattanooga, TN

Mid-level

2026-05-12

TN 2026-05-12

View full posting on CareerOneStop → ID: d1af4ea90111

Senior Data Scientist

Nelnet · Nashville, TN

Senior

2026-05-12

TN 2026-05-12

View full posting on CareerOneStop → ID: 8d82e2639cda

Senior Data Scientist

Nelnet · Frankfort, KY

Senior

2026-05-12

KY 2026-05-12

View full posting on CareerOneStop → ID: 35509c2d2c2c

Senior Machine Learning Engineer

Apex Systems · Chicago, IL

Senior

2026-05-11

IL 2026-05-11

View full posting on CareerOneStop → ID: 9667abdf01a3

AI & GenAI Data Scientist - EUR- Director

PwC · Seattle, WA

Director Master's

2026-05-10

WA 2026-05-10

Requirements

Bachelor's Degree
10 years of experience
What Sets You Apart
Master's Degree preferred
Managing AI and GenAI solution development teams
Experience in Energy and Utilities Industry
Documenting and analyzing business processes for AI
Designing AI/GenAI architectures for plugin-based solutions
Managing global data and analytics team operations
Leading development of proof of concepts and pilots
Facilitating executive level presentations on GenAI solutions
Managing GenAI application development teams
Experience with Python, LLM frameworks, and cloud platforms
The salary range for this position is: $155,000 - $410,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance

Responsibilities

Guide the strategic direction for AI and GenAI solution development
Develop and refine AI/GenAI architectures for client needs
Foster collaboration across data and analytics teams
Align with client objectives and industry standards
Promote technological advancements in data-driven solutions

View full posting on CareerOneStop → ID: a637e47c1997

Data Scientist II, Amazon Stores Security

Amazon · Seattle, WA

Mid-level Doctorate

2026-05-10

WA 2026-05-10

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Experience in Python, Perl, or another scripting language
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

Demonstrate thorough technical knowledge on feature engineering of massive datasets, effective exploratory data analysis, and model building using industry standard AI/ML models and working with Large Language Models
With your broad expertise in a variety of data science disciplines, recommend the right data science strategy and drive solution to complex or ambiguous problems
Work closely with internal stakeholders like the business teams, engineering teams and partner teams, influence their strategies to align with your focus area
Innovate by adapting new modeling techniques and procedures
Passionate about working with huge data sets ( training/fine tuning) and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets
Exposure at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive.
Show good judgment when making trade-offs between short-term customer, market, or research needs and long-term operations or technology needs.

View full posting on CareerOneStop → ID: 6ae2fbb77b15

Data Scientist II, Long Term Planning and Forecasting

Amazon · Bellevue, WA

Mid-level Doctorate

2026-05-10

WA 2026-05-10

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of guiding and coaching a group of researchers experience
1+ years of working with or evaluating AI systems experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Experience applying theoretical models in an applied environment

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in Python, Perl, or another scripting language
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience effectively communicating complex concepts through written and verbal communication
Experience in forecasting analyses

Responsibilities

As a Data Scientist in LTPF (Long-Term Planning & Forecasting):
You will develop causal inference models, automated explainability frameworks, and variance bridging methodologies that translate LTPF's forecasts and plans into actionable business intelligence.
Your work will enable leadership to understand why forecasts and actuals diverge, what is driving demand shifts, and how strategic decisions propagate through the planning ecosystem.
You will build automated Plan-vs-Actual and Actual-vs-Actual variance decomposition models that quantify the contribution of individual demand drivers to observed gaps across revenue, price, units, inventory, and capacity metrics at multiple granularities to serve audiences from working-level analysts to VP-level planning reviews cycles.
You will build and maintain a causal model library with standardized hypothesis generation and validation pipelines, applying techniques from causal inference, time-series econometrics, and Bayesian methods. Each model will include calibrated confidence scoring and reusable components that scale across worldwide marketplaces.
You will develop GenAI-powered narrative generation capabilities that synthesize quantitative variance outputs into human-readable performance summaries and design automated hypothesis ranking to determine which demand drivers are most responsible for observed forecast error.
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
Medical, Dental, and Vision Coverage
Maternity and Parental Leave Options
Paid Time Off (PTO)
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!

View full posting on CareerOneStop → ID: 39530c4e672c

Data Scientist II, Long Term Planning and Forecasting

Amazon · Bellevue, WA

Mid-level Doctorate

2026-05-10

WA 2026-05-10

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of guiding and coaching a group of researchers experience
1+ years of working with or evaluating AI systems experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Experience applying theoretical models in an applied environment

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in Python, Perl, or another scripting language
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

As a Data Scientist in LTPF (Long-Term Planning & Forecasting):
You will develop causal inference models, automated explainability frameworks, and variance bridging methodologies that translate LTPF's forecasts and plans into actionable business intelligence.
Your work will enable leadership to understand why forecasts and actuals diverge, what is driving demand shifts, and how strategic decisions propagate through the planning ecosystem.
You will build automated Plan-vs-Actual and Actual-vs-Actual variance decomposition models that quantify the contribution of individual demand drivers to observed gaps across revenue, price, units, inventory, and capacity metrics at multiple granularities to serve audiences from working-level analysts to VP-level planning reviews cycles.
You will build and maintain a causal model library with standardized hypothesis generation and validation pipelines, applying techniques from causal inference, time-series econometrics, and Bayesian methods. Each model will include calibrated confidence scoring and reusable components that scale across worldwide marketplaces.
You will develop GenAI-powered narrative generation capabilities that synthesize quantitative variance outputs into human-readable performance summaries and design automated hypothesis ranking to determine which demand drivers are most responsible for observed forecast error.
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
Medical, Dental, and Vision Coverage
Maternity and Parental Leave Options
Paid Time Off (PTO)
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!

View full posting on CareerOneStop → ID: 5953602d6eef

Principal Data Scientist & Analytics

Microsoft Corporation · Redmond, WA

Senior Doctorate

2026-05-10

WA 2026-05-10

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.

Preferred

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
Great organizational, analytical, data science skills and intuition.?
Fantastic problem solver: Ability to solve problems that the world has not solved before?
Interpersonal skills: Cross-group and cross-culture collaboration.?
Experience with real world system building and data collection, including design, coding and evaluation.??
Excellent communication to be able to communicate insights to senior leaders.
Experience with driving large collaboration across multiple teams.
Experience with communicating with different audiences to provide insights.
Demonstrated experience in applying statistics, experimentation and metrics to generate clear actionable insights.
Data Science IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Responsibilities

Product Insights: Deliver and interpret the results of analyses, validate approaches, and learn to monitor, analyze, and iterate to continuously improve products.
Measurement: Define, invent, and deliver metrics which accurately measure user and business value across various products and marketplace components.
Experimental Design & Implementation: Think critically about sampling and experimental design across User and Demand dimensions. Translate strategy into plans that are clear and measurable, with progress shared out to stakeholders.
Collaboration: Partner effectively with program management, engineers, and other areas of the business across our Consumer online business.
Influence: Engage with stakeholders to produce clear, compelling, and actionable insights and data-driven workflows that influence product and service improvements.
Make independent decisions for the team and handle difficult tradeoffs?.??
Translate strategy into plans that are clear, actionable and measurable to drive impact.

View full posting on CareerOneStop → ID: b6f3c3629b6f

AI & GenAI Data Scientist - EUR- Director

PwC · Portland, OR

Director Master's

2026-05-10

WA 2026-05-10

Requirements

Bachelor's Degree
10 years of experience
What Sets You Apart
Master's Degree preferred
Managing AI and GenAI solution development teams
Experience in Energy and Utilities Industry
Documenting and analyzing business processes for AI
Designing AI/GenAI architectures for plugin-based solutions
Managing global data and analytics team operations
Leading development of proof of concepts and pilots
Facilitating executive level presentations on GenAI solutions
Managing GenAI application development teams
Experience with Python, LLM frameworks, and cloud platforms
The salary range for this position is: $155,000 - $410,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance

Responsibilities

Guide the strategic direction for AI and GenAI solution development
Develop and refine AI/GenAI architectures for client needs
Foster collaboration across data and analytics teams
Align with client objectives and industry standards
Promote technological advancements in data-driven solutions

View full posting on CareerOneStop → ID: 8b9a9c3e88cc

AI & GenAI Data Scientist - EUR- Director

PwC · Salt Lake City, UT

Director

2026-05-10

UT 2026-05-10

View full posting on CareerOneStop → ID: 78b0843afdae

AI & GenAI Data Scientist - EUR- Director

PwC · Las Vegas, NV

Director

2026-05-10

NV 2026-05-10

View full posting on CareerOneStop → ID: fdfd8ab77b16

AI & GenAI Data Scientist - EUR- Director

PwC · Sacramento, CA

Director

2026-05-10

CA 2026-05-10

View full posting on CareerOneStop → ID: b690c49b38df

AI & GenAI Data Scientist - EUR- Director

PwC · Irvine, CA

Director

2026-05-10

CA 2026-05-10

View full posting on CareerOneStop → ID: 3c35082d6a90

AI & GenAI Data Scientist - EUR- Director

PwC · San Jose, CA

Director

2026-05-10

CA 2026-05-10

View full posting on CareerOneStop → ID: b13730babfc3

AI & GenAI Data Scientist - EUR- Director

PwC · San Diego, CA

Director

2026-05-10

CA 2026-05-10

View full posting on CareerOneStop → ID: baf59403ac51

AI & GenAI Data Scientist - EUR- Director

PwC · San Francisco, CA

Director

2026-05-10

CA 2026-05-10

View full posting on CareerOneStop → ID: c610be27eddd

AI & GenAI Data Scientist - EUR- Director

PwC · Los Angeles, CA

Director

2026-05-10

CA 2026-05-10

View full posting on CareerOneStop → ID: ee981fe1468f

AI and ML Engineer

SAIC · San Diego, CA

Mid-level

2026-05-10

CA 2026-05-10

View full posting on CareerOneStop → ID: 37eac646aaa4

Data Scientist - Predictive/AI-Driven Analytics

Insight Global · Burlingame, CA

Mid-level

2026-05-10

CA 2026-05-10

View full posting on CareerOneStop → ID: 24f89261a0f2

Principal Data Scientist - Expert Optimization, ICS Data Science

Intuit · Mountain View, CA

Senior

2026-05-10

CA 2026-05-10

View full posting on CareerOneStop → ID: 28b94880d692

Principal Data Scientist - Expert Optimization, ICS Data Science

Intuit · San Diego, CA

Senior

2026-05-10

CA 2026-05-10

View full posting on CareerOneStop → ID: a5468ccb13c8

Senior Staff Machine Learning Engineer

Intuit · Mountain View, CA

Senior

2026-05-10

CA 2026-05-10

View full posting on CareerOneStop → ID: d0986b9c8cb9

Staff Machine Learning Engineer

Intuit · Mountain View, CA

Senior

2026-05-10

CA 2026-05-10

View full posting on CareerOneStop → ID: e9ea5d943264

AI & GenAI Data Scientist - EUR- Director

PwC · Phoenix, AZ

Director

2026-05-10

AZ 2026-05-10

View full posting on CareerOneStop → ID: 622a9c54f252

AI & GenAI Data Scientist - EUR- Director

PwC · Denver, CO

Director

2026-05-10

CO 2026-05-10

View full posting on CareerOneStop → ID: 8123016d959b

Data Scientists/Business Intelligence Analyst

Talent Clustr LLC · Longmont, CO

Mid-level

2026-05-10

CO 2026-05-10

View full posting on CareerOneStop → ID: 22290aff1cc9

AI & GenAI Data Scientist - EUR- Director

PwC · Tulsa, OK

Director

2026-05-10

OK 2026-05-10

View full posting on CareerOneStop → ID: 2c1cde9bc7de

AI & GenAI Data Scientist - EUR- Director

PwC · Oklahoma City, OK

Director

2026-05-10

OK 2026-05-10

View full posting on CareerOneStop → ID: 2f43f872c6cb

AI & GenAI Data Scientist - EUR- Director

PwC · Dallas, TX

Director

2026-05-10

TX 2026-05-10

View full posting on CareerOneStop → ID: ef6f85877602

AI & GenAI Data Scientist - EUR- Director

PwC · San Antonio, TX

Director

2026-05-10

TX 2026-05-10

View full posting on CareerOneStop → ID: f3c5e6c4f7a0

AI & GenAI Data Scientist - EUR- Director

PwC · Austin, TX

Director

2026-05-10

TX 2026-05-10

View full posting on CareerOneStop → ID: 44e6156a231e

AI & GenAI Data Scientist - EUR- Director

PwC · Fort Worth, TX

Director

2026-05-10

TX 2026-05-10

View full posting on CareerOneStop → ID: b0afcf17b4bc

AI & GenAI Data Scientist - EUR- Director

PwC · Houston, TX

Director

2026-05-10

TX 2026-05-10

View full posting on CareerOneStop → ID: d2f448213ec2

Senior Machine Learning Engineer - Healthcare

MD Anderson Cancer Center · Houston, TX

Senior

2026-05-10

TX 2026-05-10

View full posting on CareerOneStop → ID: 9b166170c2e3

AI & GenAI Data Scientist - EUR- Director

PwC · Minneapolis, MN

Director

2026-05-10

MN 2026-05-10

View full posting on CareerOneStop → ID: d7ee1e2906c8

AI & GenAI Data Scientist - EUR- Director

PwC · Des Moines, IA

Director

2026-05-10

IA 2026-05-10

View full posting on CareerOneStop → ID: 147889cf8655

AI & GenAI Data Scientist - EUR- Director

PwC · Saint Louis, MO

Director

2026-05-10

MO 2026-05-10

View full posting on CareerOneStop → ID: cc96598a53e2

AI & GenAI Data Scientist - EUR- Director

PwC · Kansas City, MO

Director

2026-05-10

MO 2026-05-10

View full posting on CareerOneStop → ID: da5ddd8f64ea

AI & GenAI Data Scientist - EUR- Director

PwC · Little Rock, AR

Director

2026-05-10

AR 2026-05-10

View full posting on CareerOneStop → ID: 8bc029e40c1a

AI & GenAI Data Scientist - EUR- Director

PwC · Fayetteville, AR

Director

2026-05-10

AR 2026-05-10

View full posting on CareerOneStop → ID: 3ba1a2e33dc7

AI & GenAI Data Scientist - EUR- Director

PwC · New Orleans, LA

Director

2026-05-10

LA 2026-05-10

View full posting on CareerOneStop → ID: 7bfc4e0b36b8

AI & GenAI Data Scientist - EUR- Director

PwC · Milwaukee, WI

Director

2026-05-10

WI 2026-05-10

View full posting on CareerOneStop → ID: b757fe3e7234

Staff Machine Learning Engineer, AI Rese

CRIBL INC · Madison, WI

Senior

2026-05-10

WI 2026-05-10

View full posting on CareerOneStop → ID: c60909405c51

AI & GenAI Data Scientist - EUR- Director

PwC · Chicago, IL

Director

2026-05-10

IL 2026-05-10

View full posting on CareerOneStop → ID: 40014e37b249

AI & GenAI Data Scientist - EUR- Director

PwC · Rosemont, IL

Director

2026-05-10

IL 2026-05-10

View full posting on CareerOneStop → ID: f3e9a1f4e341

Staff Machine Learning Engineer, AI Research

Cribl, Inc · Clarksdale, MS

Senior

2026-05-10

MS 2026-05-10

View full posting on CareerOneStop → ID: c8673674717f

AI & GenAI Data Scientist - EUR- Director

PwC · Birmingham, AL

Director

2026-05-10

AL 2026-05-10

View full posting on CareerOneStop → ID: 1e7e4a9d031d

AI & GenAI Data Scientist - EUR- Director

PwC · Nashville, TN

Director

2026-05-10

TN 2026-05-10

View full posting on CareerOneStop → ID: 23a901687232

AI & GenAI Data Scientist - EUR- Director

PwC · Louisville, KY

Director

2026-05-10

KY 2026-05-10

View full posting on CareerOneStop → ID: 40d213280b7b

Machine Learning Engineer, Offline Infrastructure (Entry-Level / New Grad PhD)

Unity Technologies · Bellevue, WA

Entry-level Doctorate

2026-05-09

WA 2026-05-09

Requirements

PhD in Computer Science, Machine Learning, Systems, or a related field
Strong foundation in machine learning systems, distributed systems, or large-scale data processing (through research or projects)
Experience with Python and working with data-intensive workloads
Familiarity with ML frameworks (e.g., PyTorch, TensorFlow) and/or distributed systems (e.g., Ray, Spark)
Experience (academic or applied) with data pipelines, model training workflows, or large datasets
Strong problem-solving skills and ability to translate research ideas into practical systems
Interest in building scalable, reliable infrastructure for machine learning
Experience with workflow orchestration systems (Airflow, Flyte, etc.)
Exposure to large-scale data platforms (data lakes, warehouses, streaming systems)
Publications or research in ML systems, distributed systems, or related areas
*Additional information
Relocation support is not available for this position
Work visa/immigration sponsorship is not available for this position

Responsibilities

*The opportunity
Unity Vector builds an offline ML platform that powers insight, experimentation, attribution, and AI-driven decision-making across the company.
Our systems operate at scale across batch and streaming data, supporting analytics, product intelligence, machine learning pipelines, and business operations. As data volume and complexity grow, our platform enables large-scale model training, feature generation, and experimentation workflows that power production ML systems.
We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent PhD graduate who is excited to work on large-scale systems and apply research-driven thinking to real-world machine learning problems.
You'll help build and evolve the infrastructure that powers training data generation, ML workflows, and distributed model training. Working closely with experienced engineers and researchers, you'll contribute to systems that ensure our ML pipelines are reliable, scalable, and efficient.
This role offers the opportunity to bridge research and production-translating advanced ideas into systems that operate at scale.
Build and maintain data pipelines that generate training datasets for machine learning models and experimentation
Contribute to infrastructure that supports distributed training workflows (e.g., PyTorch, Ray)
Work with workflow orchestration tools (e.g., Airflow, Flyte, or similar) to support multi-stage ML pipelines
Improve reproducibility and reliability through dataset validation, monitoring, and testing
Partner with ML engineers to support experimentation and model iteration
Help optimize performance and efficiency across data processing and training systems
Contribute to the evolution of our offline ML platform architecture as it scales

View full posting on CareerOneStop → ID: 84abcebe5f20

Manager, Machine Learning Infrastructure - SIML

Apple · Seattle, WA

Manager Doctorate

2026-05-09

WA 2026-05-09

Requirements

Bachelor's, Master's, or Ph.D. in Computer Science, Computer Engineering, or a related field (or equivalent experience)
7+ years of software engineering experience, with 2+ years in a technical leadership or management role
Strong programming skills in one or more of: Python, Java, Go, C/C++ Solid understanding of machine learning fundamentals and ML system workflows
Proven experience in building and scaling distributed systems and backend infrastructure
Strong system design skills with expertise in at least one systems domain (e.g., data infrastructure, distributed systems, ML platforms)

Preferred

Experience building infrastructure for ML workflows (data pipelines, training systems, evaluation frameworks, or deployment systems)
Domain experience in areas such as AI/ML, computer vision, NLP, or related fields
Experience working with large-scale datasets and compute-intensive systems
Experience improving developer productivity through tooling and platform abstractions
Ability to operate effectively in cross-functional, fast-paced environments with evolving requirements

Responsibilities

Do you think Computer Vision and Machine Learning can change the world? Do you think it can transform the way millions of people collect, discover and share the most special moments of their lives? We truly believe it can. And we are looking for hardworking engineers who can contribute to building the ecosystem of tooling necessary to create these exciting technologies.
We are the System Intelligent and Machine Learning (SIML) group that provides foundational computer vision and machine learning technologies to Apple's ecosystem. Our work is behind essential features such as Camera, Text & Handwriting recognition, and Apple Intelligence experiences (Image Playground, Writing Tools, Smart Script, Math Notes..). We are seeking an Engineering Manager to lead the development of scalable, high-performance infrastructure that powers product-focused machine learning initiatives.
In this role you will lead a team responsible for building and operating infrastructure that enables large-scale data processing (terabytes and beyond) across domains such as image generation, large language models (LLMs), computer vision, natural language processing, human-computer interaction, and text recognition. This includes designing systems for dataset creation and management, ingesting annotated and inferred data, and delivering seamless access to high-quality data for ML researchers and engineers.
A key part of this role is driving systems that enable deeper understanding of model behavior-such as failure mode analysis, evaluation pipelines, and benchmarking frameworks-to accelerate iteration velocity and improve model quality. You will work across the stack, tackling challenges ranging from low-level distributed systems and compute efficiency to building stable, intuitive interfaces for internal users.
As a leader, you will partner closely with cross-functional teams including ML researchers, product teams, and platform engineering to define roadmaps, align priorities, and deliver impactful solutions. You will play a critical role in shaping how ML systems are developed, evaluated, and scaled from early experimentation to production.

View full posting on CareerOneStop → ID: d0fb3fc55c81

Senior Machine Learning Infrastructure Engineer

Unity Technologies · Bellevue, WA

Senior

2026-05-09

WA 2026-05-09

Requirements

Experience building and operating ML infrastructure or model serving systems in production
Proficiency in Golang or Python, with strong systems engineering fundamentals
Hands-on experience with Kubernetes and container orchestration at scale
Familiarity with ML serving frameworks such as Ray Serve, Triton, TorchServe, or simila
Understanding of distributed systems, API design, and system reliability
Strong collaboration and communication skills in a remote-first environment
*You might also have
Experience with feature stores, feature pipelines, or online/offline feature serving
Background in ad tech, real-time bidding, or programmatic advertising systems
Familiarity with infrastructure-as-code such as Terraform
Experience with observability tooling - Prometheus, Grafana, OpenTelemetry
Background with real-time data pipelines, caching layers, or low-latency serving systems
*Additional information
Relocation support is not available for this position

Responsibilities

*The opportunity
Unity is looking for a Senior Machine Learning Infrastructure Engineer to join our Vector Ads team, where we build the real-time systems that power Unity's global advertising platform. This is a high-scale, low-latency environment - processing billions of requests daily to deliver fast, relevant ads to players around the world.
You'll build and operate the infrastructure that brings ML models from training into production, ensuring our ranking, bidding, and targeting systems run reliably at scale. This is a great opportunity for an engineer who's excited to work at the intersection of ML systems and distributed infrastructure, collaborate across teams, and have direct impact on how machine learning shapes the player and advertiser experience.
Design, build, and maintain the infrastructure that serves ML models in real-time across Unity's ads ecosystem
Build and operate scalable model serving pipelines - owning latency, throughput, and reliability in a high-QPS production environment
Partner with ML engineers to productionize models, manage model deployments, and improve iteration speed
Improve observability, performance, and cost-efficiency of ML serving infrastructure
Contribute to architectural decisions around feature serving, model versioning, and inference optimization

View full posting on CareerOneStop → ID: b8ca15e2f6ac

Senior Machine Learning Infrastructure Engineer

Unity Technologies · Bellevue, WA

Senior

2026-05-09

WA 2026-05-09

Requirements

Experience building and operating ML infrastructure or model serving systems in production
Proficiency in Golang or Python, with strong systems engineering fundamentals
Hands-on experience with Kubernetes and container orchestration at scale
Familiarity with ML serving frameworks such as Ray Serve, Triton, TorchServe, or simila
Understanding of distributed systems, API design, and system reliability
Strong collaboration and communication skills in a remote-first environment
*You might also have
Experience with feature stores, feature pipelines, or online/offline feature serving
Background in ad tech, real-time bidding, or programmatic advertising systems
Familiarity with infrastructure-as-code such as Terraform
Experience with observability tooling - Prometheus, Grafana, OpenTelemetry
Background with real-time data pipelines, caching layers, or low-latency serving systems
*Additional information
Relocation support is not available for this position

Responsibilities

*The opportunity
Unity is looking for a Senior Machine Learning Infrastructure Engineer to join our Vector Ads team, where we build the real-time systems that power Unity's global advertising platform. This is a high-scale, low-latency environment - processing billions of requests daily to deliver fast, relevant ads to players around the world.
You'll build and operate the infrastructure that brings ML models from training into production, ensuring our ranking, bidding, and targeting systems run reliably at scale. This is a great opportunity for an engineer who's excited to work at the intersection of ML systems and distributed infrastructure, collaborate across teams, and have direct impact on how machine learning shapes the player and advertiser experience.
Design, build, and maintain the infrastructure that serves ML models in real-time across Unity's ads ecosystem
Build and operate scalable model serving pipelines - owning latency, throughput, and reliability in a high-QPS production environment
Partner with ML engineers to productionize models, manage model deployments, and improve iteration speed
Improve observability, performance, and cost-efficiency of ML serving infrastructure
Contribute to architectural decisions around feature serving, model versioning, and inference optimization

View full posting on CareerOneStop → ID: ffdf42d073cb

Software Development Engineer, Measurement, Ad Tech, and Data Science (MADS) Foundations- Traffic

Amazon · Seattle, WA

Mid-level Bachelor's

2026-05-09

WA 2026-05-09

Requirements

Expertise in large-scale distributed data processing (Spark, EMR, or equivalent)
Demonstrated ownership of end-to-end system architecture on complex, cross-team projects
Ability to influence technical decisions across organizational boundaries without direct authority
Experience operating production systems under strict SLAs at massive scale
3+ years of non-internship professional software development experience
2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
1+ years of Object Oriented Design experience
Experience programming with at least one software programming language

Preferred

3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Bachelor's degree in computer science or equivalent

Responsibilities

As a SDE , you will:
Own team architecture and lead design on multi-engineer efforts across our Spark-based EMR pipelines, decoration jobs, and publication systems
Navigate ambiguous technical problems with conflicting constraints - regulatory deadlines, performance requirements, cost targets, and cross-org dependencies
Identify one-way-door decisions, proactively address architectural deficiencies, and ensure Traffic's design doesn't limit what downstream teams can build
Drive adoption of engineering best practices and maintain sound operations - alarms, telemetry, runbooks - for a system with tier-1 SLAs
Mentor engineers, contribute to recruiting, and lead constructive technical dialog within the team and across Ads, Customer Trust, and identity-owning upstream systems
On a typical day as an Ads Traffic SDE, you might:
Start your morning with a team stand-up to align on priorities and address any blockers
Collaborate with product managers to refine requirements for upcoming features
Write code and develop solutions for complex technical challenges
Review pull requests from team members, providing constructive feedback
Participate in design discussions for new services or features
Debug and troubleshoot production issues as they arise
Attend learning sessions to stay current with Ads technologies
Document your work and contribute to technical specifications
Engage with customers or internal stakeholders to better understand their needs

View full posting on CareerOneStop → ID: b5b20b65377f

Sr Systems Development Manager, ADC Analytics and Machine Learning

Amazon · Seattle, WA

Manager Bachelor's

2026-05-09

WA 2026-05-09

Requirements

Bachelor's degree in Computer Science or a related field
Proficiency in Linux based operating systems
Experience designing, building, and operating large-scale distributed systems or web services
Experience in managing large scale infrastructure and automation
Current, active US Government Security Clearance of TS/SCI with Polygraph

Preferred

Experience delivering large-scale infrastructure products that support Tier-1 mission critical services with a focus on privacy, security, availability, and efficiency
5+ years of managing an engineering team operating at scale experience
Expertise in Linux based operating systems
Experience developing and improving operational documentation, procedures and workflows
Current, active US Government Security Clearance of Top Secret with SCI eligibility or above

Responsibilities

Build a best-in-class engineering team that delivers excellent results
Design and develop state-of-the-art approaches to solving complex and ambiguous problems
Cultivate engineering and operational excellence through metrics and continuous learning
Mentor and grow others to take on increasingly higher responsibilities
Help raise the bar on technical excellence
Show thought leadership
Communicate proficiently and concisely to different audiences

View full posting on CareerOneStop → ID: 81ea4aacf8f1

Sr. Data Scientist, Prime Video

Amazon · Seattle, WA

Senior Bachelor's

2026-05-09

WA 2026-05-09

Requirements

5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
4+ years of data scientist experience
Bachelor's degree
Experience with statistical models e.g. multinomial logistic regression

Preferred

2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
Experience managing data pipelines
Experience as a leader and mentor on a data science team

Responsibilities

Use advanced statistical and machine learning techniques to extract insights from complex, large-scale data sets
Design and implement end-to-end data science workflows, from data acquisition and cleaning to model development, testing, and deployment
Support scalable, self-service data analyses by building datasets for analytics, reporting and ML use cases
Partner with product stakeholders and science peers to identify strategic data-driven opportunities to improve the customer experience
Communicate findings, conclusions, and recommendations to technical and non-technical stakeholders
Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organization

View full posting on CareerOneStop → ID: 9a7848aa2859

Principal Data Scientist

Maximus · Olympia, WA

Senior Master's

2026-05-09

WA 2026-05-09

Requirements

'- Bachelor's degree in related field required.
10-12 years of relevant professional experience required.
Job-Specific Minimum Requirements (required skills that align with contract LCAT, verifiable, and measurable):
10+ years of relevant Software Development + AI / ML / DS experience.
Professional Programming experience (e.g. Python, R, etc.).
Experience with AI / Machine Learning.
Experience working as a contributor on a team.
Experience leading AI/DS/or Analytics teams.
Experience mentoring Junior Staff.
Experience with program management.

Preferred

Master's in quantitative discipline (Math, Operations Research, Computer Science, etc.)
Experience developing machine learning or signal processing algorithms.
Ability to leverage mathematical principles to model new and novel behaviors.
Ability to leverage statistics to identify true signals from noise or clutter.
Experience working as an individual contributor in AI or modeling and simulation.
Use of state-of-the-art technology to solve operational problems in AI, Machine Learning, or Modeling and Simulation spheres.
Strong knowledge of data structures, common computing infrastructures/paradigms (stand alone and cloud), and software engineering principles.
Ability to design custom solutions in the AI and Advanced Analytics sphere for customers. This includes the ability to scope customer needs, identify currently existing technologies, and develop custom software solutions to fill any gaps in available off the shelf solutions.
Use and development of program automation, CI/CD, DevSecOps, and Agile.
Experience managing technical teams delivering technical solutions for clients.
Experience working with optimization problems like scheduling.
Experience with Data Analytics and Visualizations.
Cloud certifications (AWS, Azure, or GCP).
10+ yrs of related experience in AI, advanced analytics, computer science, or software development.

Responsibilities

Make deep dives into the data, pulling out objective insights for business leaders.
Initiate, craft, and lead advanced analyses of operational data.
Provide a strong voice for the importance of data-driven decision making.
Provide expertise to others in data wrangling and analysis.
Convert complex data into visually appealing presentations.
Develop and deploy advanced methods to analyze operational data and derive meaningful, actionable insights for stakeholders and business development partners.
Understand the importance of automation and look to implement and initiate automated solutions where appropriate.
Initiate and take the lead on AI/ML initiatives as well as develop AI/ML code for projects.
Utilize various languages for scripting and write SQL queries. Serve as the primary point of contact for data and analytical usage across multiple projects.
Guide operational partners on product performance and solution improvement/maturity options.
Participate in intra-company data-related initiatives as well as help foster and develop relationships throughout the organization.
Learn new skills in advanced analytics/AI/ML tools, techniques, and languages.
Mentor more junior data analysts/data scientists as needed.
Apply strategic approach to lead projects from start to finish;
Develop, collaborate, and advance the applied and responsible use of AI, ML, simulation, and data science solutions throughout the enterprise and for our clients by finding the right fit of tools, technologies, processes, and automation to enable effective and efficient solutions for each unique situation.
Contribute and lead the creation, curation, and promotion of playbooks, best practices, lessons learned and firm intellectual capital.
Contribute to efforts across the enterprise to support the creation of solutions and real mission outcomes leveraging AI capabilities from Computer Vision, Natural Language Processing, LLMs and classical machine learning.
Maintain current knowledge and evaluation of the AI technology landscape and emerging developments and their applicability for use in production/operational environments.

View full posting on CareerOneStop → ID: c15502f20562

Senior AI/ML Engineer

General Motors · Olympia, WA

Senior

2026-05-09

WA 2026-05-09

Requirements

6+ years of experience building robust distributed platforms and applications.
Hands-on experience leveraging AI tools (agentic coding, search, documentation generators, etc) to accelerate understanding, implementation, debugging, and delivery of new capabilities.
Proficiency in writing and reviewing high-quality, scalable, and performant full-stack code using technologies and languages like Python, TypeScript, Go, React, SQL, Redux, GraphQL, WebGL.
Solid understanding of relational databases, data modeling, and API design.
Strong fundamentals in object-oriented design and design patterns, data structures, algorithms, and engineering best practices (TDD, code quality, observability, CI/CD).
Experience developing and operating cloud-based applications.

Preferred

Experience using modern web APIs (Service Workers, Cache Storage, IndexedDB, etc.) in data-intensive or visualization-heavy applications.
A track record of close collaboration with customers, product managers, designers, and user experience researchers.
Experience with computer vision, machine learning, or data-centric AI projects - especially where labeled data, data quality, or autolabeling loops were central to the work.
Familiarity with data labeling platforms or tools used by large labeling workforces (e.g., annotation UIs, workflow engines, quality systems).
Experience with A/B testing and telemetry/observability systems to measure impact and reliability.
Proficiency in writing and reviewing high-quality, scalable, and performant code using TypeScript, React, Redux, GraphQL, WebGL, or similar frontend technologies.
_Compensation_ : The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.
The salary range for this roleis $170,600 to $261,300.The actual basesalarya successful candidate will be offered within this range will vary based on factors relevant to the position.
Bonus Potential: An incentivepayprogram offers payouts based on company performance, job level, and individual performance.
Benefits: GM offers a variety of health and wellbeing benefit programs.Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuitionassistanceprograms, employeeassistanceprogram, GM vehicle discounts and more.

Responsibilities

_Remote/Hybrid:_ _This role is based remotely but if you live within a 50-mile radius of Sunnyvale, CA_ _you_ _are expected to report to that location three times a week._
Help teach our self-driving vehicles how to see and understand the world!
The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling tools and pipelines that power autonomous vehicle machine learning models within General Motors' AV organization.
We operate in the intersection of software engineering, data engineering, and AI/ML, defining the strategies, tooling, and quality controls that create reliable training data at scale. Our tools and platform are used by thousands of users and consumers.
We own a modern full-stack architecture including TypeScript/React, Python, GraphQL, Golang, and ML model services, which powers data-annotation pipelines and machine-led training data solutions at foundation-model scale. We partner closely across AI/ML engineers, Product Operations, Product Management, Data Science, and other ML Platform groups.
This role is ideal for an engineer who wants end-to-end ownership of meaningful pieces of the platform, growth toward technical leadership, and direct impact on systems that unblock the next generation of AV capabilities.
Build high-impact labeling experiences Design, implement, and test scalable, high-performance user experiences and services using modern full-stack and/or frontend technologies. You'll ship features spanning multiple surface-areas that directly affect how quickly and accurately we can label data for new models and cities.
Level up how ML teams work with data Develop automation and tooling that give ML engineers deep insight into labeling workflows and data quality (e.g., efficiency dashboards, auto-QA, autolabel review tools), reducing iteration time from idea to trained model.
Apply ML to labeling itself Collaborate with ML engineers to design and integrate ML-driven data annotation (pre-labeling, autolabeling, active learning loops), helping us move from human-only to machine-led labeling at scale.
Champion AI-assisted engineering Use and advocate for modern AI-powered development workflows (code assistants, automated documentation, test generation, etc.) to increase velocity while maintaining quality.
Own projects end-to-end Take ownership of technical projects from problem framing through design, implementation, and rollout. Drive code reviews, design discussions, and technical decisions.
Collaborate across the AV stack Work with partner teams (ML, Ops, Product, Data Science, other platform teams) to translate abstract requirements into concrete workflows, APIs, and UIs that hit quality, cost, and latency goals.
*Your Skills & Abilities
Passionate about self-driving technology and its potential to transform safety, mobility, and the driving experience.
Driven to learn new technologies and deepen your expertise across frontend, backend, and data/ML-adjacent systems.
Proven experience shipping and operating end-to-end products or features in production.
Strong communication and collaboration skills; you can explain tradeoffs, influence peers, and work through ambiguity with cross-functional partners.
Empathetic to user challenges (from labelers to ML engineers to Ops) and excited to turn messy workflows into simple, intuitive tools.

View full posting on CareerOneStop → ID: 9780206c5c6d

Technical Project Manager - Machine Learning & Data Science

Cadmus · Olympia, WA

Manager Bachelor's

2026-05-09

WA 2026-05-09

Requirements

5+ years of experience as a Technical Project Manager or Scrum Master, managing cross-functional projects.
Bachelor's degree in Information Systems, BI or Analytics or Engineering.
Strong technical proficiency and experience working with Machine Learning (ML) or Data Science/Artificial Intelligence (DS/AI) teams.
Experience managing large, ambiguous, cross-functional programs operating in fast-paced, highly collaborative environments.
Experience performing TPM best practices (e.g., schedule development and tracking, risk management, status reporting).
Experience regularly maintaining and reporting program data, preferably in Jira.
Deep understanding of Agile and SDLC methodologies and leading/modeling process adherence.
Excellent communication and problem-solving skills.
Ability to facilitate teams and individuals working collaboratively and efficiently.
A composed presence, business acumen, and ability to communicate at multiple levels of the organization.
Experience with automation and/or AI tools such as ChatGPT, Gemini, etc.
Preferred certifications: PMP or Scrum Master.
*Additional Information:
Candidates must be eligible to work in the United States as a U.S Perm Resident or U.S. Citizen.

Responsibilities

Manage and coordinate across multiple engineering teams delivering Machine Learning (ML) and Data Science/Artificial Intelligence (DS/AI) features and capabilities to support the broader vision, goals, and objectives of the company. Coordinate activities with internal teams and external partners.
Oversee end-to-end activities to ensure coordination and on-time delivery. Build integrated schedules based on an understanding team's activities and interdependencies between teams. Manage removing blockers, risks, and issues. Report program status.
Lead Agile ceremonies and assist with story definition, backlog prioritization, and dependency resolution.
Help Engineering teams balance scope, timeline, and quality to achieve optimal outcomes based on an understanding of priorities.
Advocate for clear priorities, technical excellence, process and best practices adherence, and customer-focused outcomes.
Influence without authority and drive consensus across diverse stakeholders.

View full posting on CareerOneStop → ID: 61a801000082

Principal Data Scientist

Maximus · Boise, ID

Senior

2026-05-09

ID 2026-05-09

View full posting on CareerOneStop → ID: de63f43ed315

Senior AI/ML Engineer

General Motors · Boise, ID

Senior

2026-05-09

ID 2026-05-09

View full posting on CareerOneStop → ID: f879aeaecbe5

Technical Project Manager - Machine Learning & Data Science

Cadmus · Boise, ID

Manager

2026-05-09

ID 2026-05-09

View full posting on CareerOneStop → ID: cf89a8291802

Principal Data Scientist

Maximus · Salem, OR

Senior

2026-05-09

OR 2026-05-09

View full posting on CareerOneStop → ID: 70e48a27d19f

Senior AI/ML Engineer

General Motors · Salem, OR

Senior

2026-05-09

OR 2026-05-09

View full posting on CareerOneStop → ID: 553636f711d5

Technical Project Manager - Machine Learning & Data Science

Cadmus · Salem, OR

Manager

2026-05-09

OR 2026-05-09

View full posting on CareerOneStop → ID: c698c99d5e8a

Principal Data Scientist

Maximus · Helena, MT

Senior

2026-05-09

MT 2026-05-09

View full posting on CareerOneStop → ID: 37ada9473574

Senior AI/ML Engineer

General Motors · Helena, MT

Senior

2026-05-09

MT 2026-05-09

View full posting on CareerOneStop → ID: be3f4ab94bbf

Technical Project Manager - Machine Learning & Data Science

Cadmus · Helena, MT

Manager

2026-05-09

MT 2026-05-09

View full posting on CareerOneStop → ID: fbc3bdcb768b

Principal Data Scientist

Maximus · Cheyenne, WY

Senior

2026-05-09

WY 2026-05-09

View full posting on CareerOneStop → ID: 541bb6ac8607

Senior AI/ML Engineer

General Motors · Cheyenne, WY

Senior

2026-05-09

WY 2026-05-09

View full posting on CareerOneStop → ID: 4f1e31ac9ee1

Technical Project Manager - Machine Learning & Data Science

Cadmus · Cheyenne, WY

Manager

2026-05-09

WY 2026-05-09

View full posting on CareerOneStop → ID: 9d7297b806a8

Principal Data Scientist

Maximus · Salt Lake City, UT

Senior

2026-05-09

UT 2026-05-09

View full posting on CareerOneStop → ID: 7400b52d4867

Senior AI/ML Engineer

General Motors · Salt Lake City, UT

Senior

2026-05-09

UT 2026-05-09

View full posting on CareerOneStop → ID: 58e7d3211fd1

Summer Undergrad Data Science Intern

University of Utah · Salt Lake City, UT

Intern

2026-05-09

UT 2026-05-09

View full posting on CareerOneStop → ID: 1fe6358096be

Technical Project Manager - Machine Learning & Data Science

Cadmus · Salt Lake City, UT

Manager

2026-05-09

UT 2026-05-09

View full posting on CareerOneStop → ID: 0506b0505022

Principal Data Scientist

Maximus · Carson City, NV

Senior

2026-05-09

NV 2026-05-09

View full posting on CareerOneStop → ID: b3c8c220b117

Senior AI/ML Engineer

General Motors · Carson City, NV

Senior

2026-05-09

NV 2026-05-09

View full posting on CareerOneStop → ID: 78097a90166b

Technical Project Manager - Machine Learning & Data Science

Cadmus · Carson City, NV

Manager

2026-05-09

NV 2026-05-09

View full posting on CareerOneStop → ID: cc6d645b5e79

Principal Data Scientist

Maximus · Bismarck, ND

Senior

2026-05-09

ND 2026-05-09

View full posting on CareerOneStop → ID: d91976b7e522

Senior AI/ML Engineer

General Motors · Bismarck, ND

Senior

2026-05-09

ND 2026-05-09

View full posting on CareerOneStop → ID: 120f2ab5fcf5

Technical Project Manager - Machine Learning & Data Science

Cadmus · Bismarck, ND

Manager

2026-05-09

ND 2026-05-09

View full posting on CareerOneStop → ID: 79d40124f546

Principal Data Scientist

Maximus · Pierre, SD

Senior

2026-05-09

SD 2026-05-09

View full posting on CareerOneStop → ID: 4adb5f8c9e08

Senior AI/ML Engineer

General Motors · Pierre, SD

Senior

2026-05-09

SD 2026-05-09

View full posting on CareerOneStop → ID: 70f9f6de8d47

Technical Project Manager - Machine Learning & Data Science

Cadmus · Pierre, SD

Manager

2026-05-09

SD 2026-05-09

View full posting on CareerOneStop → ID: 2e70b08f25f3

Data Scientist

Zoom · San Jose, CA

Mid-level

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 4b47557e12b0

Data Scientist III - AMZ9803634

Amazon · San Diego, CA

Mid-level

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 9da6a32e1597

Lead AI/ML Engineer (Platform, kubeflow)

Capital One · San Francisco, CA

Senior

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: f81673e9059a

Lead AI/ML Engineer (Platform, kubeflow)

Capital One · San Jose, CA

Senior

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 8b6312c0800c

Machine Learning Engineer - Agentic AI

Apple · Sunnyvale, CA

Mid-level

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 0ec92f4171ae

Machine Learning Engineer, Offline Infrastructure (Entry-Level / New Grad PhD)

Unity Technologies · San Francisco, CA

Entry-level

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 3fe4cc1bcfd4

Machine Learning Engineer, Offline Infrastructure (Entry-Level / New Grad PhD)

Unity Technologies · Mountain View, CA

Entry-level

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: df268a01a178

Manager, Machine Learning Infrastructure - SIML

Apple · Cupertino, CA

Manager

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 23a872893084

Principal Data Scientist

Maximus · Sacramento, CA

Senior

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: f435e1b9e497

Senior AI/ML Engineer

General Motors · Sunnyvale, CA

Senior

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 705119f81b7b

Senior AI/ML Engineer

General Motors · Sacramento, CA

Senior

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 47159d5b53e4

Senior Machine Learning Infrastructure Engineer

Unity Technologies · Mountain View, CA

Senior

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 49f720dd910b

Senior Machine Learning Infrastructure Engineer

Unity Technologies · Mountain View, CA

Senior

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 9e141a9e666b

Senior Machine Learning Infrastructure Engineer

Unity Technologies · San Francisco, CA

Senior

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: f8f3cd3671fb

Senior Manager, Data Science - LLM Customization Team

Capital One · San Jose, CA

Manager

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 75b470169089

Senior Product Data Scientist, Devices Insights and Analytics

Google · Mountain View, CA

Senior

2026-05-09

CA 2026-05-09

View full posting on CareerOneStop → ID: 41906a789bb0

Principal Data Scientist

Maximus · Phoenix, AZ

Senior

2026-05-09

AZ 2026-05-09

View full posting on CareerOneStop → ID: 84edbe39a454

Senior AI/ML Engineer

General Motors · Phoenix, AZ

Senior

2026-05-09

AZ 2026-05-09

View full posting on CareerOneStop → ID: f784c02d0b14

Technical Project Manager - Machine Learning & Data Science

Cadmus · Phoenix, AZ

Manager

2026-05-09

AZ 2026-05-09

View full posting on CareerOneStop → ID: b6ebd2f63311

Principal Data Scientist

Maximus · Santa Fe, NM

Senior

2026-05-09

NM 2026-05-09

View full posting on CareerOneStop → ID: bbba5faf245d

Senior AI/ML Engineer

General Motors · Santa Fe, NM

Senior

2026-05-09

NM 2026-05-09

View full posting on CareerOneStop → ID: 9d0343598485

Technical Project Manager - Machine Learning & Data Science

Cadmus · Santa Fe, NM

Manager

2026-05-09

NM 2026-05-09

View full posting on CareerOneStop → ID: a2cc8052a938

Principal Data Scientist

Maximus · Denver, CO

Senior

2026-05-09

CO 2026-05-09

View full posting on CareerOneStop → ID: 7ad6fb80fc41

Senior AI/ML Engineer

General Motors · Denver, CO

Senior

2026-05-09

CO 2026-05-09

View full posting on CareerOneStop → ID: 1810bfbeef48

Technical Project Manager - Machine Learning & Data Science

Cadmus · Denver, CO

Manager

2026-05-09

CO 2026-05-09

View full posting on CareerOneStop → ID: 99b75ea021f4

Principal Data Scientist

Maximus · Lincoln, NE

Senior

2026-05-09

NE 2026-05-09

View full posting on CareerOneStop → ID: 57f21cf683e0

Senior AI/ML Engineer

General Motors · Lincoln, NE

Senior

2026-05-09

NE 2026-05-09

View full posting on CareerOneStop → ID: 3cd076b61d81

Technical Project Manager - Machine Learning & Data Science

Cadmus · Lincoln, NE

Manager

2026-05-09

NE 2026-05-09

View full posting on CareerOneStop → ID: b9ee6c6930db

Principal Data Scientist

Maximus · Topeka, KS

Senior

2026-05-09

KS 2026-05-09

View full posting on CareerOneStop → ID: ce3729c56014

Senior AI/ML Engineer

General Motors · Topeka, KS

Senior

2026-05-09

KS 2026-05-09

View full posting on CareerOneStop → ID: 5c0281bf2915

Technical Project Manager - Machine Learning & Data Science

Cadmus · Topeka, KS

Manager

2026-05-09

KS 2026-05-09

View full posting on CareerOneStop → ID: 11fedb997984

Principal Data Scientist

Maximus · Oklahoma City, OK

Senior

2026-05-09

OK 2026-05-09

View full posting on CareerOneStop → ID: 1d5c3b05be5f

Senior AI/ML Engineer

General Motors · Oklahoma City, OK

Senior

2026-05-09

OK 2026-05-09

View full posting on CareerOneStop → ID: a46454387bee

Technical Project Manager - Machine Learning & Data Science

Cadmus · Oklahoma City, OK

Manager

2026-05-09

OK 2026-05-09

View full posting on CareerOneStop → ID: 53e6e1816b1a

Machine Learning Engineering - Intelligent Foundations and Experiences (IFX)

Capital One · Plano, TX

Mid-level

2026-05-09

TX 2026-05-09

View full posting on CareerOneStop → ID: c316424c03f4

Principal Data Scientist

Maximus · Austin, TX

Senior

2026-05-09

TX 2026-05-09

View full posting on CareerOneStop → ID: 9bf37fd33de0

Principal Data Scientist

Toyota · Plano, TX

Senior

2026-05-09

TX 2026-05-09

View full posting on CareerOneStop → ID: 7c5b9d9f3ed2

Senior AI/ML Engineer

General Motors · Austin, TX

Senior

2026-05-09

TX 2026-05-09

View full posting on CareerOneStop → ID: 00cea3f6494e

Senior Lead Machine Learning Engineer

Capital One · Plano, TX

Senior

2026-05-09

TX 2026-05-09

View full posting on CareerOneStop → ID: ae87fb67835f

Senior Manager, Data Science - Credit Review

Capital One · Plano, TX

Manager

2026-05-09

TX 2026-05-09

View full posting on CareerOneStop → ID: 08a9129e239d

Associate AI/ML Engineer - AI Program

Mayo Clinic · Rochester, MN

Entry-level

2026-05-09

MN 2026-05-09

View full posting on CareerOneStop → ID: 1fc9000dcf7c

Associate Data Science Analyst - AI Program

Mayo Clinic · Rochester, MN

Entry-level

2026-05-09

MN 2026-05-09

View full posting on CareerOneStop → ID: 68ce77fb824f

Data Scientist Specialist

3M · Maplewood, MN

Mid-level

2026-05-09

MN 2026-05-09

View full posting on CareerOneStop → ID: ebcf2986c683

Principal Data Scientist

Maximus · Saint Paul, MN

Senior

2026-05-09

MN 2026-05-09

View full posting on CareerOneStop → ID: 7288f2deb40f

Principal Data Scientist - Remote

UnitedHealth Group · Eden Prairie, MN

Senior

2026-05-09

MN 2026-05-09

View full posting on CareerOneStop → ID: 448af67f0002

Principal Data Scientist - Remote

UnitedHealth Group · Eden Prairie, MN

Senior

2026-05-09

MN 2026-05-09

View full posting on CareerOneStop → ID: e786e0d01968

Senior AI/ML Engineer

General Motors · Saint Paul, MN

Senior

2026-05-09

MN 2026-05-09

View full posting on CareerOneStop → ID: c5e99217f83a

Senior Data Science Analyst - AI Program

Mayo Clinic · Rochester, MN

Senior

2026-05-09

MN 2026-05-09

View full posting on CareerOneStop → ID: 3a9a122eaef7

Technical Project Manager - Machine Learning & Data Science

Cadmus · Saint Paul, MN

Manager

2026-05-09

MN 2026-05-09

View full posting on CareerOneStop → ID: c17ea691a624

Principal Data Scientist

Maximus · Des Moines, IA

Senior

2026-05-09

IA 2026-05-09

View full posting on CareerOneStop → ID: 6457614ec3f6

Senior AI/ML Engineer

General Motors · Des Moines, IA

Senior

2026-05-09

IA 2026-05-09

View full posting on CareerOneStop → ID: 2d3c8c6136b4

Technical Project Manager - Machine Learning & Data Science

Cadmus · Des Moines, IA

Manager

2026-05-09

IA 2026-05-09

View full posting on CareerOneStop → ID: 4c016d5f93c7

Principal Data Scientist

Maximus · Jefferson City, MO

Senior

2026-05-09

MO 2026-05-09

View full posting on CareerOneStop → ID: 3b69e6f69ec6

Protein Design Data Scientist Postdoc

Bayer · Chesterfield, MO

Mid-level

2026-05-09

MO 2026-05-09

View full posting on CareerOneStop → ID: 0fad867a01b1

Senior AI/ML Engineer

General Motors · Jefferson City, MO

Senior

2026-05-09

MO 2026-05-09

View full posting on CareerOneStop → ID: 88810b777595

Technical Project Manager - Machine Learning & Data Science

Cadmus · Jefferson City, MO

Manager

2026-05-09

MO 2026-05-09

View full posting on CareerOneStop → ID: b8e3d50af012

Principal Data Scientist

Maximus · Little Rock, AR

Senior

2026-05-09

AR 2026-05-09

View full posting on CareerOneStop → ID: b40ed98d44e9

Senior AI/ML Engineer

General Motors · Little Rock, AR

Senior

2026-05-09

AR 2026-05-09

View full posting on CareerOneStop → ID: 1f8d7561e029

Staff, Data Scientist

Walmart · Bentonville, AR

Senior

2026-05-09

AR 2026-05-09

View full posting on CareerOneStop → ID: 7ea2ab4e8ce9

Technical Project Manager - Machine Learning & Data Science

Cadmus · Little Rock, AR

Manager

2026-05-09

AR 2026-05-09

View full posting on CareerOneStop → ID: 713517ce4320

Principal Data Scientist

Maximus · Baton Rouge, LA

Senior

2026-05-09

LA 2026-05-09

View full posting on CareerOneStop → ID: ea7a99146019

Senior AI/ML Engineer

General Motors · Baton Rouge, LA

Senior

2026-05-09

LA 2026-05-09

View full posting on CareerOneStop → ID: 560608c9e610

Technical Project Manager - Machine Learning & Data Science

Cadmus · Baton Rouge, LA

Manager

2026-05-09

LA 2026-05-09

View full posting on CareerOneStop → ID: 71d45038859f

Principal Data Scientist

Maximus · Madison, WI

Senior

2026-05-09

WI 2026-05-09

View full posting on CareerOneStop → ID: 3ba6ffd890af

Senior AI/ML Engineer

General Motors · Madison, WI

Senior

2026-05-09

WI 2026-05-09

View full posting on CareerOneStop → ID: 24331b80ff97

Technical Project Manager - Machine Learning & Data Science

Cadmus · Madison, WI

Manager

2026-05-09

WI 2026-05-09

View full posting on CareerOneStop → ID: d99cbbf4ddea

AI/ML Engineer - Remote

UnitedHealth Group · Schaumburg, IL

Mid-level

2026-05-09

IL 2026-05-09

View full posting on CareerOneStop → ID: eb982f95098f

Manager, Data Scientist - US Card DFS Acquisitions

Capital One · Chicago, IL

Manager

2026-05-09

IL 2026-05-09

View full posting on CareerOneStop → ID: 626dd48ed2d3

Principal Data Scientist

Maximus · Springfield, IL

Senior

2026-05-09

IL 2026-05-09

View full posting on CareerOneStop → ID: e091201e185b

Senior AI/ML Engineer

General Motors · Springfield, IL

Senior

2026-05-09

IL 2026-05-09

View full posting on CareerOneStop → ID: 9d13d825747e

Senior Manager, Data Science - Credit Review

Capital One · Riverwoods, IL

Manager

2026-05-09

IL 2026-05-09

View full posting on CareerOneStop → ID: a10d7323b705

Senior Manager, Data Science - Model Risk Office

Capital One · Chicago, IL

Manager

2026-05-09

IL 2026-05-09

View full posting on CareerOneStop → ID: 8859d0d6e11b

Technical Project Manager - Machine Learning & Data Science

Cadmus · Springfield, IL

Manager

2026-05-09

IL 2026-05-09

View full posting on CareerOneStop → ID: d61ecd1528a1

Principal Data Scientist

Maximus · Jackson, MS

Senior

2026-05-09

MS 2026-05-09

View full posting on CareerOneStop → ID: 441ef15a54c6

Senior AI/ML Engineer

General Motors · Jackson, MS

Senior

2026-05-09

MS 2026-05-09

View full posting on CareerOneStop → ID: 646433690080

Technical Project Manager - Machine Learning & Data Science

Cadmus · Jackson, MS

Manager

2026-05-09

MS 2026-05-09

View full posting on CareerOneStop → ID: e967eaecf112

Data Scientist

Actalent · Birmingham, AL

Mid-level

2026-05-09

AL 2026-05-09

View full posting on CareerOneStop → ID: 5c2b31583b30

Principal Data Scientist

Maximus · Montgomery, AL

Senior

2026-05-09

AL 2026-05-09

View full posting on CareerOneStop → ID: b2aec3bc3cb8

Senior AI/ML Engineer

General Motors · Montgomery, AL

Senior

2026-05-09

AL 2026-05-09

View full posting on CareerOneStop → ID: 56ac2f2bb59b

Technical Project Manager - Machine Learning & Data Science

Cadmus · Montgomery, AL

Manager

2026-05-09

AL 2026-05-09

View full posting on CareerOneStop → ID: d17262f13c4f

Principal Data Scientist

Maximus · Nashville, TN

Senior

2026-05-09

TN 2026-05-09

View full posting on CareerOneStop → ID: 9895802fcbc8

Senior AI/ML Engineer

General Motors · Nashville, TN

Senior

2026-05-09

TN 2026-05-09

View full posting on CareerOneStop → ID: 111da7592fa8

senior manager, Data Science (Nashville, TN)

Starbucks · Nashville, TN

Manager

2026-05-09

TN 2026-05-09

View full posting on CareerOneStop → ID: 14de9b7d79c0

Technical Project Manager - Machine Learning & Data Science

Cadmus · Nashville, TN

Manager

2026-05-09

TN 2026-05-09

View full posting on CareerOneStop → ID: fd355074ffac

Machine Learning Detection Engineer (Remote, East/Central)

CrowdStrike, Inc. · Frankfort, KY

Mid-level

2026-05-09

KY 2026-05-09

View full posting on CareerOneStop → ID: b317294f6436

Principal Data Scientist

Maximus · Frankfort, KY

Senior

2026-05-09

KY 2026-05-09

View full posting on CareerOneStop → ID: 59fb39454c9f

Senior AI/ML Engineer

General Motors · Frankfort, KY

Senior

2026-05-09

KY 2026-05-09

View full posting on CareerOneStop → ID: 6a18d9be0937

Technical Project Manager - Machine Learning & Data Science

Cadmus · Frankfort, KY

Manager

2026-05-09

KY 2026-05-09

View full posting on CareerOneStop → ID: 2f8b5d238c39

Data Scientist, Advertising, AMPI Measurement

Amazon · Seattle, WA

Mid-level

2026-05-09

WA 2026-05-09

View full posting on CareerOneStop → ID: caf75b34e747

Data Scientist, WW Ops FP&A

Amazon · Bellevue, WA

Mid-level Doctorate

2026-05-08

WA 2026-05-08

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of guiding and coaching a group of researchers experience
1+ years of working with or evaluating AI systems experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Experience applying theoretical models in an applied environment

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

Own and solve difficult business problems where the solution approach is unclear, delivering high-quality artifacts that directly influence financial decisions for senior leadership
Apply a range of data science methodologies (statistical modeling, machine learning, time series analysis, econometrics) to solve complex forecasting challenges
Design and implement scalable, reliable approaches to extract insights from large, complex datasets across multiple domains
Develop metrics to quantify the benefits of solutions and measure project progress and success
Design and implement Retrieval-Augmented Generation (RAG) systems and LLM-based solutions to enhance financial knowledge retrieval and decision support
Proactively identify and solve challenges related to GenAI solutions including accuracy, latency, and context management
Partner with finance stakeholders, engineers, and other scientists to identify data requirements and deliver solutions that meet customer needs
Write clear, factually correct documents with substantial analytical components; explain technical concepts to non-technical audiences
Provide peer feedback on solutions and results; mentor and teach less experienced data scientists

View full posting on CareerOneStop → ID: 3ec0f3cbe7a2

Machine Learning Engineer, Search & Knowledge Quality

Apple · Seattle, WA

Mid-level Doctorate

2026-05-08

WA 2026-05-08

Requirements

BSc or Masters degree in Machine Learning, Data Science, Computer Science, Information Security, Mathematics, Statistics, or related field.
3+ years of industry related experience, working in collaborate environments
Experience with programming skills in Python,C/C++, GoLand
Experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, AXLearn and Scikit-learn.
Familiarity with integrating ML solutions into production systems and existing workflows at scale; experience with CI/CD workflows and ML pipelines .
Excellent written and verbal communication skills, with the ability to present technical concepts clearly to varied audiences.
Strong problem-solving skills and ability to work independently as well as in a team environment.

Preferred

Ph.D. in a related field.
Experience with state-of-the-art ML methodologies, including LLM fine-tuning, neural network optimization , RL
Strong communication and accountability skills; a hard-working, strong work ethic, and collaboration abilities.
Experimental rigor when training/evaluating LLMs for the purpose of benchmarking LLM optimization algorithms.

Responsibilities

The Search and Knowledge Quality team is redefining how hundreds of millions of users interact with their devices to access information. We are an Applied Machine Learning team pushing the boundaries of artificial intelligence-from query understanding and information retrieval to response ranking and contextual answer generation.
Our team drives innovation by conducting research, building end-to-end solutions, and deploying them at scale to deliver meaningful customer impact across Apple products.
In this role, you will leverage and advance state-of-the-art LLM and ML techniques to better understand user queries and intent, improve document ranking, and generate high-quality answers. You will have end-to-end ownership of features within the Siri Search system, from ideation through production deployment. You will collaborate with industry-leading experts and cross-functional teams across multiple geographies, tackling complex challenges at scale.

View full posting on CareerOneStop → ID: 182f9a6dd20c

Manager, Data Science, Outbound Communications

Amazon · Seattle, WA

Manager Master's

2026-05-08

WA 2026-05-08

Requirements

5+ years of building quantitative solutions as a scientist or science manager experience
2+ years of scientists or machine learning engineers management experience
5+ years of applying statistical models for large-scale application and building automated analytical systems experience
Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
Knowledge of Python or R or other scripting language

Preferred

Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems

Responsibilities

You will lead applied scientists, data scientists and business intelligence engineers to:
Optimize Outbound's inbox management and planning system to personalize frequency, send-time and relevance bar of our messages to customers.
Design and execute large-scale experiments such as multi-arm elasticity tests or RCTs to measure and improve incrementality/performance of our models.
Drive development of HVA propensity models (opt-out, purchase, etc.) to drive intended behavior of customers to their next stage of shopping and engagement with Amazon.
Drive AI-based transformation in data accuracy and reporting: migrating and enhancing the self-serve analytics capabilities developed by the team, automating WBR preparation, building anomaly detection, etc.
Own financial planning frameworks for outbound performance including QxG/HVE forecasting and ROI measurement for paid channel investments.
In addition, you will:
Hire, develop, and mentor scientists and BIEs while partnering cross-functionally with engineering, product, marketing, and partner science teams (CBA, P13N, CFV) to productionize solutions at scale.
Create, align and evolve your team's roadmap by prioritizing across multiple competing priorities using high judgement decisions.

View full posting on CareerOneStop → ID: 1db4bc78fe2e

Principal Data Scientist

Microsoft Corporation · Redmond, WA

Senior Doctorate

2026-05-08

WA 2026-05-08

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.

Preferred

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
10+ years of hands-on experience with cloud data platforms (e.g., Azure, AWS or Google etc.).
10+ years of programming experience in Python , SQL Server , and PySpark , including understanding and maintaining scalable data pipelines and machine learning models.
10+ years of hands-on experience translating business requirements into data-driven solutions using ML algorithms (e.g., classification, regression, clustering, NLP etc.).
2+ year of experience in PowerBI reporting and SSAS is a plus
2+ year of experience in business planning is plus.
Strong communication skills and ability to collaborate across cross-functional teams.
Experience managing stakeholder and leader communications effectively.
Experience in quota modeling, incentive compensation, or sales analytics and forecast is a plus.
Proven ability to mentor junior data scientists and lead end-to-end ML lifecycle projects.
Hands-on experience with cloud platforms and tools such as Azure Synapse and Azure Foundry , with a focus on developing and deploying AI models is a plus.
Experience designing, building, or deploying agentic AI systems - including autonomous agents, multi-agent orchestration, tool-use frameworks, or agent-based workflows using platforms such as LangChain, AutoGen, Semantic Kernel, or similar is a plus.
Data Science IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Responsibilities

The Principal Data Scientist is responsible for the following:
*Business Management:
Defines quota-setting strategy aligned with business, customer, and solution objectives. Partners cross-functionally to identify and pursue opportunities for applying machine learning and other data-science methods to quota and incentive design.
Bridges Finance, Sales, Business Sales Operations, and Product teams through deep technical expertise. Drives cross-discipline collaboration and leads efforts to refine intellectual property definitions and methodology improvements.
Educates field managers and sales leaders on quota methodology, data inputs, and model mechanics through roadshows, workshops, and ongoing enablement - ensuring transparency and building trust in the quota-setting process.
*Business Understanding and Impact
Applies deep domain expertise to analyze challenges across product lines, identifying and mitigating risks that could influence quota outcomes.
Partners with business stakeholders to shape strategy, recommend improvements, and surface opportunities to extend existing work into new contexts. Establishes and promotes standards and best practices across teams.
*Coding and Debugging:
Writes efficient, readable, and extensible code and models spanning multiple features and solutions. Contributes to code and model reviews with actionable feedback, and maintains strong expertise in modeling, coding, and debugging techniques - including isolating and resolving errors and defects.
Leads project teams in gathering, integrating, and interpreting data from multiple sources to troubleshoot issues end-to-end. Provides feedback to product groups on non-optimized features and explores potential for new capabilities.
Brings expert-level proficiency in big-data and ML engineering tools and practices, including Hadoop, Apache Spark, CI/CD, Docker, Delta Lake, MLflow, Azure ML, and REST API development.
*Customer/Partner Orientation
Maintains a customer-first mindset - understanding stakeholder needs, validating their perspectives, and serving as a trusted advisor within the broader organizational context.
Adds strategic value by connecting business understanding, product functionality, data sources, and methodology expertise to reframe problems and deliver actionable insights. Leads customer discussions and offers pragmatic solutions that account for real-world data limitations.
*Modeling and Statistical Analysis :
Generalizes ML solutions into repeatable frameworks - modules, packages, and general-purpose tools - for broader team reuse. Enforces team standards for bias, privacy, and ethics. Reviews teammates' model methodology and performance, recommending improvements where appropriate.
Anticipates risks such as data leakage, bias/variance tradeoffs, and methodological limitations, guiding teammates toward sound solutions. Drives best practices in model validation, implementation, and deployment. Develops operational models that run reliably at scale.
Partners cross-functionally to identify opportunities for ML and predictive analysis. Uncovers new customer scenarios for transformative ML-driven solutions while incorporating AI ethics best practices. Maintains deep, current expertise in emerging AI/ML methodologies.
*Data Preparation and Understanding :
Oversees data acquisition and ensures datasets are properly formatted and accurately documented. Uses SQL, Python, and visualization tools to explore data - analyzing distributions, attribute relationships, sub-population properties, and statistical summaries.
Builds data platforms from scratch across product lines. Designs data-science business solutions using established technologies, patterns, and practices. Provides guidance on operationalizing models created by data scientists.
Identifies new opportunities from data and processes it for general-purpose use. Contributes to thought leadership and IP on data acquisition best practices. Leads resolution of data-integrity issues.
*Evaluating for Insights and Impact:
Conducts thorough reviews of analytical techniques and processes, highlighting gaps or areas needing reexamination. Uses assessment findings to determine next steps - deployment, further iteration, or new project directions.
Ensures clear alignment between selected models and business objectives, validating that model outputs drive meaningful outcomes.
Defines and designs feedback loops and evaluation methods to measure ongoing model impact.
*Coach and Mentoring:
Mentors engineers on data cleaning, analysis best practices, and ethical data handling. Identifies gaps in existing datasets and drives onboarding of new sources, including third-party data. Champions ethics and privacy discussions, integrating industry-wide insights to influence internal processes and decision-making.
Maintains strong proficiency in the Microsoft AI/ML toolset (Azure Machine Learning, Azure Cognitive Services, Azure Databricks). Translates complex statistical and ML concepts into accessible explanations for customers and stakeholders.
Embody our culture (https://careers.microsoft.com/us/en/culture) and values (https://www.microsoft.com/en-us/about/corporate-values) .

View full posting on CareerOneStop → ID: 73859e80bcee

Staff Machine Learning Engineer, AI Research

Cribl, Inc · Tumwater, WA

Senior

2026-05-08

WA 2026-05-08

B2B SAAS data observability software. Join the company that's building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world's biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructur

View full posting on CareerOneStop → ID: 4d6190be1f87

Data Scientist

Sedgwick · Boise, ID

Mid-level

2026-05-08

ID 2026-05-08

View full posting on CareerOneStop → ID: e96aaff3185d

Staff Machine Learning Engineer, AI Research

Cribl, Inc · Helena, MT

Senior

2026-05-08

MT 2026-05-08

View full posting on CareerOneStop → ID: 2b13773fa023

Data Scientist

Sedgwick · Cheyenne, WY

Mid-level

2026-05-08

WY 2026-05-08

View full posting on CareerOneStop → ID: 85bbf619229d

Data Scientist I - AI/ML

COTIVITI, INC. · South Jordan, UT

Entry-level

2026-05-08

UT 2026-05-08

View full posting on CareerOneStop → ID: faf02744f67e

Sr. Staff Data Scientist

Northrop Grumman · Clearfield, UT

Senior

2026-05-08

UT 2026-05-08

View full posting on CareerOneStop → ID: d5ed5e334bb5

Data Scientist

Sedgwick · Las Vegas, NV

Mid-level

2026-05-08

NV 2026-05-08

View full posting on CareerOneStop → ID: 84dfc1748f8e

Data Scientist

Sedgwick · Carson City, NV

Mid-level

2026-05-08

NV 2026-05-08

View full posting on CareerOneStop → ID: dcdd4b2c19f9

Data Scientist

Sedgwick · Bismarck, ND

Mid-level

2026-05-08

ND 2026-05-08

View full posting on CareerOneStop → ID: ece7580bbe03

Data Scientist

Sedgwick · Fargo, ND

Mid-level

2026-05-08

ND 2026-05-08

View full posting on CareerOneStop → ID: 928c77c69133

Data Scientist

Sedgwick · Sioux Falls, SD

Mid-level

2026-05-08

SD 2026-05-08

View full posting on CareerOneStop → ID: d37c8ec6bf4c

Data Scientist

Sedgwick · Rapid City, SD

Mid-level

2026-05-08

SD 2026-05-08

View full posting on CareerOneStop → ID: cc3c3a7d1f74

Data Scientist

Sedgwick · Pierre, SD

Mid-level

2026-05-08

SD 2026-05-08

View full posting on CareerOneStop → ID: cd8d14f91cd7

Data Scientist

Sedgwick · Flagstaff, AZ

Mid-level

2026-05-08

AZ 2026-05-08

View full posting on CareerOneStop → ID: 71f9e0c9c769

Data Scientist

Sedgwick · Phoenix, AZ

Mid-level

2026-05-08

AZ 2026-05-08

View full posting on CareerOneStop → ID: 9bbf3d2aee3b

Data Scientist

Sedgwick · Tucson, AZ

Mid-level

2026-05-08

AZ 2026-05-08

View full posting on CareerOneStop → ID: c71683df86e9

Data Scientist

Sedgwick · Albuquerque, NM

Mid-level

2026-05-08

NM 2026-05-08

View full posting on CareerOneStop → ID: 9c9819a4aa9e

Data Scientist

Sedgwick · Santa Fe, NM

Mid-level

2026-05-08

NM 2026-05-08

View full posting on CareerOneStop → ID: a140b5884af6

Data Scientist

Sedgwick · Lincoln, NE

Mid-level

2026-05-08

NE 2026-05-08

View full posting on CareerOneStop → ID: d0ca31486c33

Data Scientist

Sedgwick · Omaha, NE

Mid-level

2026-05-08

NE 2026-05-08

View full posting on CareerOneStop → ID: db980686deb6

Data Scientist

Sedgwick · Topeka, KS

Mid-level

2026-05-08

KS 2026-05-08

View full posting on CareerOneStop → ID: 2b890c03a28c

Data Scientist

Sedgwick · Wichita, KS

Mid-level

2026-05-08

KS 2026-05-08

View full posting on CareerOneStop → ID: 0d347e4baf28

Data Scientist

Sedgwick · Overland Park, KS

Mid-level

2026-05-08

KS 2026-05-08

View full posting on CareerOneStop → ID: dc358097a569

Data Scientist

Sedgwick · Bartlesville, OK

Mid-level

2026-05-08

OK 2026-05-08

View full posting on CareerOneStop → ID: 814c31a60edb

Data Scientist

Sedgwick · Tulsa, OK

Mid-level

2026-05-08

OK 2026-05-08

View full posting on CareerOneStop → ID: bf4765775900

Data Scientist

Sedgwick · Oklahoma City, OK

Mid-level

2026-05-08

OK 2026-05-08

View full posting on CareerOneStop → ID: dd8da892d9eb

Director, Data Science - AI Product & Risk

UnitedHealth Group · Minnetonka, MN

Director

2026-05-08

MN 2026-05-08

View full posting on CareerOneStop → ID: c7e3c98dba80

Sr. Director, AI/ML Engineering - Remote

UnitedHealth Group · Eden Prairie, MN

Director

2026-05-08

MN 2026-05-08

View full posting on CareerOneStop → ID: b49fc32b6fbe

Data Scientist

Sedgwick · Coralville, IA

Mid-level

2026-05-08

IA 2026-05-08

View full posting on CareerOneStop → ID: d3df06fffc70

Data Scientist

Sedgwick · Dubuque, IA

Mid-level

2026-05-08

IA 2026-05-08

View full posting on CareerOneStop → ID: d21fa2bbd1f1

Data Scientist

Sedgwick · Des Moines, IA

Mid-level

2026-05-08

IA 2026-05-08

View full posting on CareerOneStop → ID: 0639927e39de

Data Scientist

Sedgwick · Cedar Rapids, IA

Mid-level

2026-05-08

IA 2026-05-08

View full posting on CareerOneStop → ID: f125515fe03e

Data Scientist

Sedgwick · Saint Louis, MO

Mid-level

2026-05-08

MO 2026-05-08

View full posting on CareerOneStop → ID: 05b12a03fe76

Data Scientist

Sedgwick · Kansas City, MO

Mid-level

2026-05-08

MO 2026-05-08

View full posting on CareerOneStop → ID: acde8c0a6a78

Data Scientist

Sedgwick · Jefferson City, MO

Mid-level

2026-05-08

MO 2026-05-08

View full posting on CareerOneStop → ID: c51041d8ae22

Data Scientist

Sedgwick · Little Rock, AR

Mid-level

2026-05-08

AR 2026-05-08

View full posting on CareerOneStop → ID: 0666aff08b9e

Senior, Data Scientist - Membership Insights (Contact Center)

Walmart · Bentonville, AR

Senior

2026-05-08

AR 2026-05-08

View full posting on CareerOneStop → ID: 816bb2ef72d3

Data Scientist

Sedgwick · Shreveport, LA

Mid-level

2026-05-08

LA 2026-05-08

View full posting on CareerOneStop → ID: 02490aed6860

Data Scientist

Sedgwick · Baton Rouge, LA

Mid-level

2026-05-08

LA 2026-05-08

View full posting on CareerOneStop → ID: 311df3ed69e2

Data Scientist

Sedgwick · New Orleans, LA

Mid-level

2026-05-08

LA 2026-05-08

View full posting on CareerOneStop → ID: 0614391270da

Data Scientist

Sedgwick · Wausau, WI

Mid-level

2026-05-08

WI 2026-05-08

View full posting on CareerOneStop → ID: 1b9e5295d90e

Data Scientist

Sedgwick · Madison, WI

Mid-level

2026-05-08

WI 2026-05-08

View full posting on CareerOneStop → ID: 5ce8fb4671bc

Data Scientist

Sedgwick · Milwaukee, WI

Mid-level

2026-05-08

WI 2026-05-08

View full posting on CareerOneStop → ID: 9019dd4191ac

Data Scientist II (Remote)

Kohl's · Menomonee Falls, WI

Mid-level

2026-05-08

WI 2026-05-08

View full posting on CareerOneStop → ID: 19a4d21c2ec9

AI Engineer / Data Scientist, AI Sr. Manager

PwC · Chicago, IL

Manager

2026-05-08

IL 2026-05-08

View full posting on CareerOneStop → ID: d4c45f66dfb1

Senior Data Scientist

Loyola University Chicago · Chicago, IL

Senior

2026-05-08

IL 2026-05-08

View full posting on CareerOneStop → ID: 925649c43c0a

Data Scientist

Sedgwick · Jackson, MS

Mid-level

2026-05-08

MS 2026-05-08

View full posting on CareerOneStop → ID: 2d9fae4a0dda

Data Scientist

Sedgwick · Biloxi, MS

Mid-level

2026-05-08

MS 2026-05-08

View full posting on CareerOneStop → ID: 9ecce23896e6

Data Scientist

Sedgwick · Southaven, MS

Mid-level

2026-05-08

MS 2026-05-08

View full posting on CareerOneStop → ID: ebcf3c42d6d5

Data Scientist

Sedgwick · Mobile, AL

Mid-level

2026-05-08

AL 2026-05-08

View full posting on CareerOneStop → ID: 46189fe191cd

Data Scientist

Sedgwick · Montgomery, AL

Mid-level

2026-05-08

AL 2026-05-08

View full posting on CareerOneStop → ID: 890371efd73a

Data Scientist

Sedgwick · Birmingham, AL

Mid-level

2026-05-08

AL 2026-05-08

View full posting on CareerOneStop → ID: fd1b30003c39

Data Scientist

Sedgwick · Knoxville, TN

Mid-level

2026-05-08

TN 2026-05-08

View full posting on CareerOneStop → ID: 41ae017aa06a

Data Scientist

Sedgwick · Memphis, TN

Mid-level

2026-05-08

TN 2026-05-08

View full posting on CareerOneStop → ID: c0c00ec846c7

Data Scientist

Sedgwick · Nashville, TN

Mid-level

2026-05-08

TN 2026-05-08

View full posting on CareerOneStop → ID: f85e6a2b5a73

Data Scientist

Sedgwick · Lexington, KY

Mid-level

2026-05-08

KY 2026-05-08

View full posting on CareerOneStop → ID: f88fbbf3cc19

Data Scientist

Sedgwick · Frankfort, KY

Mid-level

2026-05-08

KY 2026-05-08

View full posting on CareerOneStop → ID: 06d524022996

Data Scientist

Sedgwick · Louisville, KY

Mid-level

2026-05-08

KY 2026-05-08

View full posting on CareerOneStop → ID: 20467bb1c7b1

Staff Machine Learning Engineer, AI Research

Cribl, Inc · Frankfort, KY

Senior

2026-05-08

KY 2026-05-08

View full posting on CareerOneStop → ID: e55d2ad592fc

Data Scientist/Analytics V

Applied Materials · Santa Clara, CA

Mid-level

2026-05-08

WA 2026-05-08

View full posting on CareerOneStop → ID: eae5f7b27a71

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Seattle, WA

Manager Master's

2026-05-07

WA 2026-05-07

Requirements

A Bachelor's degree required (4-year degree).
6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning
2-4 years of experience directly managing technical teams
Strong skills in Python
Ability lead, collaborate, and communicate effectively with diverse, hybrid and global teams
Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform
Proficient in Generative AI models and frameworks (e.g., OpenAI, Dall-e, Langchain, Retrieval Augmented Generation (RAG)) and experienced with ML packages like scikit-learn and PyTorch
Experience with natural language processing and deep learning
Extensive experience in DevOps tools (GIT, Azure DevOps), Agile methodologies (Jira), and CI/CD pipelines for developing, deploying, and scaling analytical solutions
Experience with MLOps and ML workflows, including data ingestion, transformation, and evaluation
Experience with model retraining and feedback loop methodologies
Experience with model and solution monitoring and reporting
Understanding of data structures, data modelling and software engineering best practices
Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques
Excellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements
Skills in Technical Design Optimization
Strong relationship-building skills
Demonstrated client trust and value
Digital fluency and emotional agility
Commercial acumen and negotiation skills
Proven ability to lead teams and manage change
Experience delivering analytics or AI solutions in asset-intensive environments (e.g., utilities, energy, infrastructure, manufacturing, or transportation) is strongly preferred.
Familiarity with utility regulatory, compliance, or operational data considerations is a plus.
*Ideally, you'll also have
A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them
Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field
Experience working with diverse teams to deliver complex solutions
Strong skills in languages beyond Python: R, JavaScript, Java, C++, C
Experience fine-tuning Generative AI models
Experience in managing complex projects with multiple stakeholders
A strong understanding of industry trends and emerging technologies
Skills in data visualization and storytelling with data
Experience with image processing techniques and/or speech and audio processing and analysis
Exposure to Power & Utilities transformation programs, such as grid modernization, advanced metering, wildfire mitigation, energy transition, DER integration, or digital operations initiatives.
Experience supporting executive-level decision-making in regulated environments, including preparation of materials that may be reviewed by regulators or governing bodies.
*What we look fo
We seek individuals who are not only technically proficient but also possess the ability to think critically and creatively. Top performers demonstrate a commitment to excellence, a collaborative spirit, and a passion for driving innovation in the field of AI and data science. Your ability to collaborate effectively and communicate with clarity will set you apart as a leader in our team.
In the Power & Utilities sector, we value leaders who can balance innovation with reliability, speed with safety, and advanced analytics with regulatory and operational realities delivering AI solutions that utilities can trust, scale, and defend.

Responsibilities

As a Manager in AI Native Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver the latest data science and big data technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support the ongoing business needs of our clients.
You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry.
In Power & Utilities contexts, this includes working with business, IT, and operations leaders to translate regulated utility priorities-such as safety, reliability, affordability, and compliance-into scalable AI-enabled solutions.
Leading workstream delivery and ensuring the effective management of processes and projects.
Continuously improving processes by identifying innovative solutions through research and analysis.
Managing professional employees and supervising teams to deliver complex technical initiatives, with accountability for performance and results.
Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure.
Identifying opportunities for additional services and managing engagement economics.
Designing and delivering AI/ML use cases relevant to Power & Utilities, such as asset health and failure prediction, outage detection and restoration optimization, vegetation management analytics, demand forecasting, load and DER forecasting, predictive maintenance, customer operations optimization, and regulatory analytics.
Working with utility data sources including SCADA, AMI/AMI 2.0, GIS, EAM (e.g., Maximo), OMS, CIS, and historian systems, and integrating these into modern analytics platforms.
Supporting utilities in moving AI solutions from pilots to production while meeting regulatory, audit, cybersecurity, and data governance requirements.
*Skills and attributes for success
To excel in this role, you will need a blend of technical expertise and strong interpersonal skills. This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services
For Power & Utilities clients, success also requires an understanding of regulated operating models, risk tolerance, safety culture, rate cases, capital programs, and long asset lifecycles, and the ability to align AI outcomes to these realities.
The following attributes will make a significant impact:
Proven ability to develop solutions to complex problems and recommend changes to policies and procedures.
Strong judgment in selecting methods and techniques for obtaining results.
Experience in managing client relationships and delivering high-quality service.
Ability to lead teams effectively and manage change within the organization.
Ability to translate AI and analytics outputs into business-relevant insights for utility executives, regulators, and operational leaders.
Comfort operating in highly regulated environments with strong governance, documentation, explainability, and model risk management expectations.

View full posting on CareerOneStop → ID: 686e59cf50a7

Data Scientist

Capgemini · Seattle, WA

Mid-level

2026-05-07

WA 2026-05-07

Requirements

Design, develop, and deploy AI enabled applications aligned to enterprise needs.
Translate business problems into scalable technical solutions.
Build Generative AI solutions using large language models, including RAG and tool enabled workflows.
Apply AI assisted code generation and developer productivity tools for tasks such as code scaffolding, refactoring, documentation, and test generation.
Design and integrate application components using REST APIs, authentication, error handling, and observability best practices.
Deploy and operate AI solutions in production or production adjacent environments, supporting monitoring and reliability.
The base compensation range for this role in the posted location is $70,000- $110,000
Contract Type: Permanent
Seattle, WA, US
Brand: Capgemini
Professional Community: Data & AI

Responsibilities

Capgemini is building a Seattle-based AI Cohort to support strategic enterprise engagements focused on Generative AI, intelligent applications, and advanced analytics. This role combines hands-on AI engineering with a delivery and consulting oriented mindset. You will work closely with business and technical stakeholders to shape, build, and scale AI solutions from early exploration through production delivery. Some engagements may follow a Forward Deployment Engineer (FDE)-style working model, where engineers collaborate closely with client teams during solution design and rollout. However, the role remains broad and well suited for candidates who enjoy combining strong technical problem solving with collaborative, client facing delivery. Many initiatives are centered on enterprise cloud and AI platforms, with a strong preference for Azure based architectures and services, as well as modern developer environments that incorporate AI assisted development and code generation tools.

View full posting on CareerOneStop → ID: c46630f27b7d

Data Scientist, AWS Quick Data

Amazon · Seattle, WA

Mid-level Doctorate

2026-05-07

WA 2026-05-07

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of working with or evaluating AI systems experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Experience applying theoretical models in an applied environment

Preferred

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions.
Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features
Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings
Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases
Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance
Develop and refine annotation guidelines and quality frameworks for evaluation tasks
Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies
Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements
Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts
Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets

View full posting on CareerOneStop → ID: 451bab6bcd6d

Research Data Scientist, Chrome

Google · Seattle, WA

Mid-level Doctorate

2026-05-07

WA 2026-05-07

Requirements

Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.

Preferred

5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.

Responsibilities

Chrome's mission is to make the web work better for you. We do this by evolving Chrome, which serves the world and Google as both a product (4 billion plus clients) and a platform (that is: Chromium and related components that advance the open web and open media technologies).
As a platform, Chrome envisions a fast, safe, capable platform and thriving web for generations of users and developers. As a product, Chrome imagines a more helpful, adaptive agent that helps people with their multifaceted needs. Chrome's goal is to redefine browsing by delivering unparalleled safety, speed, efficiency, and ease of use, and integrating with Generative Artificial Intelligence (GenAI) and Google's web products, to understand user needs and provide personalized experiences.
In this role, your work will have tremendous impact throughout Chrome, as you will have an opportunity to work with the many teams that use our systems to gate features and understand users.You will blend research and product expertise to manage issues.
You will leverage a mix of theoretical and practical knowledge in advanced statistical and machine learning (ML) techniques, predictive modeling, human evaluation, experimentation, forecasting, exploratory analysis, and more to drive data-informed innovation, unlock opportunities, and enhance user experiences within Chrome.The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Leverage advanced statistical methods on massive, datasets to extract insights from billions of events and thousands of features across organizational sources.
Analyze intricate product and platform usage patterns, translating data-driven insights into actionable product strategy and engineering decisions.
Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
Navigate technical or methodological conversations and narrative-telling presentations. Make clear, concise product and engineering recommendations to drive major impact. Use coding and methodology.
Demonstrate an interest and aptitude in data, metrics, analysis, and trends, and applied knowledge of measurement, statistics, and program evaluation.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 45c9a2be5971

Senior Data Scientist - AI & ML | MLOps Enablement (Hybrid - Seattle, WA)

Nordstrom · Seattle, WA

Senior Doctorate

2026-05-07

WA 2026-05-07

Responsibilities

The Developer Platform Organization's mission is to accelerate the delivery of reliable and secure platforms that make developers feel good and code their best. Developer Platform exists to help engineers focus on business challenges and minimize their work on infrastructure and operations - developing and supporting platforms and tools for the entire Software Development Lifecycle. Centralized platform tooling allows developer tooling to be written once, and not repeated for each team or project.
Within Developer Platform, the MLOps Enablement team owns the ML Platform capability. Data Scientists and engineers can build, deploy, and operate machine learning models on managed, standards-compliant infrastructure - without standing up their own model serving or ML pipeline tooling. We deliver a unified, secure, and cost-efficient platform built on Vertex AI.
We are looking for a Senior Data Scientist to join the MLOps Enablement team as an embedded DS practitioner. This is not a traditional Data Science role focused on owning models - it is a platform-facing role for a DS practitioner who wants to shape the infrastructure and tooling that Data Scientists across Nordstrom depend on every day. You will be the DS voice on a platform engineering team, ensuring our capabilities are designed for how Data Scientists actually work - so adoption is fast, intuitive, and does not require a custom engagement every time.
This role is offered as hybrid in Seattle, WA. Candidates must be available to work in office at the Nordstrom corporate headquarters a minimum of 4 days/week to be considered for this position.
Run end-to-end POC validation for new platform capabilities - Feature Store, Endpoints, Model Evaluation, AutoML, BigQuery ML etc. - independently, before they reach DS teams at scale
Attend DS team planning and design sessions as an embedded practitioner; surface real workflow pain points and translate them into reusable MLOps platform requirements
Design and own the Model Evaluation Framework - defining metrics, thresholds, and evaluation pipelines for batch, online, and streaming use cases on Vertex AI
Build model-type-aware Feature Store schemas, endpoint configurations, and evaluation pipelines that accommodate the fundamentally different needs of different ML models
Lead benchmarking of Nordstrom's platform against industry standards - SageMaker vs. Vertex AI - across feature parity, cost, and DS practitioner ergonomics
Author DS-native documentation, onboarding guides, and quickstart notebooks that lower the adoption barrier for new platform features
Contribute DS domain expertise to the emerging Vertex AI Agentic Platform - identifying DS workflow pain points as agent use cases and defining evaluation frameworks for agentic responses
Own model card standards - capturing what actually matters to a practitioner, not just governance checkboxes
Communicate complex trade-offs and platform decisions to technical and non-technical stakeholders across DS, engineering, and leadership
You own this if you have...
Bachelor's, Master's, or PhD in Statistics, Data Science, Computer Science, Engineering, or a related technical field required
10+ years of hands-on Data Science experience with production model delivery across multiple ML (classification, ranking, NLP, time-series, recommendation) and GenAI models
Deep expertise in model evaluation - defining metrics, thresholds, and evaluation pipelines for real-world production models
Experience with Feature Store design, feature engineering, and understanding of feature freshness, reuse, and drift across different model families
Proficiency in Python with experience writing clean, maintainable, production-quality ML code
Strong understanding of ML monitoring - data drift, prediction drift, and concept drift detection
Experience with experiment tracking and model lifecycle management
Ability to translate between DS practice and platform engineering - comfortable driving design decisions, authoring DS-native documentation, and engaging in technical design reviews
Self-directed; comfortable owning POC work end-to-end without a dedicated DS team structure
Hands-on experience with GCP and Vertex AI - Workbench, Pipelines, Feature Store, Model Endpoints, Model Registry, Model Evaluation (preferred)
Familiarity with AWS SageMaker for cross-cloud benchmarking and comparison context (preferred)
Understanding of CI/CD for ML, containerization, and pipeline orchestration - able to engage at platform depth alongside MLOps engineers (preferred)
Prior experience in ML platform adoption, enablement, or developer experience work (preferred)
Experience operating within a mature ML lifecycle - versioning, lineage tracking, model governance, staged rollouts, and model deprecation practices at enterprise scale (preferred)
Exposure to agentic AI patterns, LLM evaluation frameworks, or Vertex AI Agent Builder (preferred)
We've got you covered...
Our employees are our most important asset and that's reflected in our benefits. Nordstrom is proud to offer a variety of benefits to support employees and their families, including:
Medical/Vision, Dental, Retirement and Paid Time Away

View full posting on CareerOneStop → ID: 68244860eb58

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Olympia, WA

Manager Master's

2026-05-07

WA 2026-05-07

Requirements

A Bachelor's degree required (4-year degree).
6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning
2-4 years of experience directly managing technical teams
Strong skills in Python
Ability lead, collaborate, and communicate effectively with diverse, hybrid and global teams
Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform
Proficient in Generative AI models and frameworks (e.g., OpenAI, Dall-e, Langchain, Retrieval Augmented Generation (RAG)) and experienced with ML packages like scikit-learn and PyTorch
Experience with natural language processing and deep learning
Extensive experience in DevOps tools (GIT, Azure DevOps), Agile methodologies (Jira), and CI/CD pipelines for developing, deploying, and scaling analytical solutions
Experience with MLOps and ML workflows, including data ingestion, transformation, and evaluation
Experience with model retraining and feedback loop methodologies
Experience with model and solution monitoring and reporting
Understanding of data structures, data modelling and software engineering best practices
Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques
Excellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements
Skills in Technical Design Optimization
Strong relationship-building skills
Demonstrated client trust and value
Digital fluency and emotional agility
Commercial acumen and negotiation skills
Proven ability to lead teams and manage change
Experience delivering analytics or AI solutions in asset-intensive environments (e.g., utilities, energy, infrastructure, manufacturing, or transportation) is strongly preferred.
Familiarity with utility regulatory, compliance, or operational data considerations is a plus.
*Ideally, you'll also have
A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them
Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field
Experience working with diverse teams to deliver complex solutions
Strong skills in languages beyond Python: R, JavaScript, Java, C++, C
Experience fine-tuning Generative AI models
Experience in managing complex projects with multiple stakeholders
A strong understanding of industry trends and emerging technologies
Skills in data visualization and storytelling with data
Experience with image processing techniques and/or speech and audio processing and analysis
Exposure to Power & Utilities transformation programs, such as grid modernization, advanced metering, wildfire mitigation, energy transition, DER integration, or digital operations initiatives.
Experience supporting executive-level decision-making in regulated environments, including preparation of materials that may be reviewed by regulators or governing bodies.
*What we look fo
We seek individuals who are not only technically proficient but also possess the ability to think critically and creatively. Top performers demonstrate a commitment to excellence, a collaborative spirit, and a passion for driving innovation in the field of AI and data science. Your ability to collaborate effectively and communicate with clarity will set you apart as a leader in our team.
In the Power & Utilities sector, we value leaders who can balance innovation with reliability, speed with safety, and advanced analytics with regulatory and operational realities delivering AI solutions that utilities can trust, scale, and defend.

Responsibilities

As a Manager in AI Native Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver the latest data science and big data technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support the ongoing business needs of our clients.
You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry.
In Power & Utilities contexts, this includes working with business, IT, and operations leaders to translate regulated utility priorities-such as safety, reliability, affordability, and compliance-into scalable AI-enabled solutions.
Leading workstream delivery and ensuring the effective management of processes and projects.
Continuously improving processes by identifying innovative solutions through research and analysis.
Managing professional employees and supervising teams to deliver complex technical initiatives, with accountability for performance and results.
Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure.
Identifying opportunities for additional services and managing engagement economics.
Designing and delivering AI/ML use cases relevant to Power & Utilities, such as asset health and failure prediction, outage detection and restoration optimization, vegetation management analytics, demand forecasting, load and DER forecasting, predictive maintenance, customer operations optimization, and regulatory analytics.
Working with utility data sources including SCADA, AMI/AMI 2.0, GIS, EAM (e.g., Maximo), OMS, CIS, and historian systems, and integrating these into modern analytics platforms.
Supporting utilities in moving AI solutions from pilots to production while meeting regulatory, audit, cybersecurity, and data governance requirements.
*Skills and attributes for success
To excel in this role, you will need a blend of technical expertise and strong interpersonal skills. This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services
For Power & Utilities clients, success also requires an understanding of regulated operating models, risk tolerance, safety culture, rate cases, capital programs, and long asset lifecycles, and the ability to align AI outcomes to these realities.
The following attributes will make a significant impact:
Proven ability to develop solutions to complex problems and recommend changes to policies and procedures.
Strong judgment in selecting methods and techniques for obtaining results.
Experience in managing client relationships and delivering high-quality service.
Ability to lead teams effectively and manage change within the organization.
Ability to translate AI and analytics outputs into business-relevant insights for utility executives, regulators, and operational leaders.
Comfort operating in highly regulated environments with strong governance, documentation, explainability, and model risk management expectations.

View full posting on CareerOneStop → ID: d43ded705913

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Portland, OR

Manager Master's

2026-05-07

WA 2026-05-07

Requirements

A Bachelor's degree required (4-year degree).
6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning
2-4 years of experience directly managing technical teams
Strong skills in Python
Ability lead, collaborate, and communicate effectively with diverse, hybrid and global teams
Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform
Proficient in Generative AI models and frameworks (e.g., OpenAI, Dall-e, Langchain, Retrieval Augmented Generation (RAG)) and experienced with ML packages like scikit-learn and PyTorch
Experience with natural language processing and deep learning
Extensive experience in DevOps tools (GIT, Azure DevOps), Agile methodologies (Jira), and CI/CD pipelines for developing, deploying, and scaling analytical solutions
Experience with MLOps and ML workflows, including data ingestion, transformation, and evaluation
Experience with model retraining and feedback loop methodologies
Experience with model and solution monitoring and reporting
Understanding of data structures, data modelling and software engineering best practices
Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques
Excellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements
Skills in Technical Design Optimization
Strong relationship-building skills
Demonstrated client trust and value
Digital fluency and emotional agility
Commercial acumen and negotiation skills
Proven ability to lead teams and manage change
Experience delivering analytics or AI solutions in asset-intensive environments (e.g., utilities, energy, infrastructure, manufacturing, or transportation) is strongly preferred.
Familiarity with utility regulatory, compliance, or operational data considerations is a plus.
*Ideally, you'll also have
A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them
Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field
Experience working with diverse teams to deliver complex solutions
Strong skills in languages beyond Python: R, JavaScript, Java, C++, C
Experience fine-tuning Generative AI models
Experience in managing complex projects with multiple stakeholders
A strong understanding of industry trends and emerging technologies
Skills in data visualization and storytelling with data
Experience with image processing techniques and/or speech and audio processing and analysis
Exposure to Power & Utilities transformation programs, such as grid modernization, advanced metering, wildfire mitigation, energy transition, DER integration, or digital operations initiatives.
Experience supporting executive-level decision-making in regulated environments, including preparation of materials that may be reviewed by regulators or governing bodies.
*What we look fo
We seek individuals who are not only technically proficient but also possess the ability to think critically and creatively. Top performers demonstrate a commitment to excellence, a collaborative spirit, and a passion for driving innovation in the field of AI and data science. Your ability to collaborate effectively and communicate with clarity will set you apart as a leader in our team.
In the Power & Utilities sector, we value leaders who can balance innovation with reliability, speed with safety, and advanced analytics with regulatory and operational realities delivering AI solutions that utilities can trust, scale, and defend.

Responsibilities

As a Manager in AI Native Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver the latest data science and big data technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support the ongoing business needs of our clients.
You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry.
In Power & Utilities contexts, this includes working with business, IT, and operations leaders to translate regulated utility priorities-such as safety, reliability, affordability, and compliance-into scalable AI-enabled solutions.
Leading workstream delivery and ensuring the effective management of processes and projects.
Continuously improving processes by identifying innovative solutions through research and analysis.
Managing professional employees and supervising teams to deliver complex technical initiatives, with accountability for performance and results.
Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure.
Identifying opportunities for additional services and managing engagement economics.
Designing and delivering AI/ML use cases relevant to Power & Utilities, such as asset health and failure prediction, outage detection and restoration optimization, vegetation management analytics, demand forecasting, load and DER forecasting, predictive maintenance, customer operations optimization, and regulatory analytics.
Working with utility data sources including SCADA, AMI/AMI 2.0, GIS, EAM (e.g., Maximo), OMS, CIS, and historian systems, and integrating these into modern analytics platforms.
Supporting utilities in moving AI solutions from pilots to production while meeting regulatory, audit, cybersecurity, and data governance requirements.
*Skills and attributes for success
To excel in this role, you will need a blend of technical expertise and strong interpersonal skills. This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services
For Power & Utilities clients, success also requires an understanding of regulated operating models, risk tolerance, safety culture, rate cases, capital programs, and long asset lifecycles, and the ability to align AI outcomes to these realities.
The following attributes will make a significant impact:
Proven ability to develop solutions to complex problems and recommend changes to policies and procedures.
Strong judgment in selecting methods and techniques for obtaining results.
Experience in managing client relationships and delivering high-quality service.
Ability to lead teams effectively and manage change within the organization.
Ability to translate AI and analytics outputs into business-relevant insights for utility executives, regulators, and operational leaders.
Comfort operating in highly regulated environments with strong governance, documentation, explainability, and model risk management expectations.

View full posting on CareerOneStop → ID: 8925bf24e604

Principal / Staff Reliability Engineer - Statistics & Data Science

Micron Technology, Inc. · Boise, ID

Senior

2026-05-07

ID 2026-05-07

View full posting on CareerOneStop → ID: 7084fb8bdfea

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Salem, OR

Manager

2026-05-07

OR 2026-05-07

View full posting on CareerOneStop → ID: 04d793fa540b

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Salt Lake City, UT

Manager

2026-05-07

UT 2026-05-07

View full posting on CareerOneStop → ID: 950eb3d6f74b

Machine Learning Engineer

PLURALSIGHT, LLC · Draper, UT

Mid-level

2026-05-07

UT 2026-05-07

View full posting on CareerOneStop → ID: 5e2e5d6a13bd

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Las Vegas, NV

Manager

2026-05-07

NV 2026-05-07

View full posting on CareerOneStop → ID: 62a66b78decd

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Carson City, NV

Manager

2026-05-07

NV 2026-05-07

View full posting on CareerOneStop → ID: 767fb86be729

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Tucson, AZ

Manager

2026-05-07

AZ 2026-05-07

View full posting on CareerOneStop → ID: b235b1a58dcf

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Phoenix, AZ

Manager

2026-05-07

AZ 2026-05-07

View full posting on CareerOneStop → ID: 2acad43ac117

GenAI Data Scientist

Deloitte · Gilbert, AZ

Mid-level

2026-05-07

AZ 2026-05-07

View full posting on CareerOneStop → ID: d45daf0357bf

GenAI Data Scientist

Deloitte · Gilbert, AZ

Mid-level

2026-05-07

AZ 2026-05-07

View full posting on CareerOneStop → ID: d717ecce1e17

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Topeka, KS

Manager

2026-05-07

KS 2026-05-07

View full posting on CareerOneStop → ID: 4f615c95db8e

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Wichita, KS

Manager

2026-05-07

KS 2026-05-07

View full posting on CareerOneStop → ID: dfc4dcb32d09

Data Scientists/BI Developer

Staffingtree, Inc. · Overland Park, KS

Mid-level

2026-05-07

KS 2026-05-07

View full posting on CareerOneStop → ID: 9c95b7a9b22f

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Oklahoma City, OK

Manager

2026-05-07

OK 2026-05-07

View full posting on CareerOneStop → ID: 69f41d7b91cc

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Tulsa, OK

Manager

2026-05-07

OK 2026-05-07

View full posting on CareerOneStop → ID: c52ad09241a2

DATA SCIENTIST-DIRECT HIRE AUTHORITY

U.S. Air Force - Agency Wide · Oklahoma City, OK

Mid-level

2026-05-07

OK 2026-05-07

View full posting on CareerOneStop → ID: ac7e6bba3451

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Saint Paul, MN

Manager

2026-05-07

MN 2026-05-07

View full posting on CareerOneStop → ID: c9108111713a

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Minneapolis, MN

Manager

2026-05-07

MN 2026-05-07

View full posting on CareerOneStop → ID: f567fa15204c

Lead AI/ML Engineer

TEKsystems · Minneapolis, MN

Senior

2026-05-07

MN 2026-05-07

View full posting on CareerOneStop → ID: 697c682dae95

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Des Moines, IA

Manager

2026-05-07

IA 2026-05-07

View full posting on CareerOneStop → ID: 00679a8c0d15

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Kansas City, MO

Manager

2026-05-07

MO 2026-05-07

View full posting on CareerOneStop → ID: a6ac77a76df9

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Saint Louis, MO

Manager

2026-05-07

MO 2026-05-07

View full posting on CareerOneStop → ID: 3e73471ba07a

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Jefferson City, MO

Manager

2026-05-07

MO 2026-05-07

View full posting on CareerOneStop → ID: 599a110bc887

Machine Learning Scientist

Bayer · Saint Louis, MO

Mid-level

2026-05-07

MO 2026-05-07

View full posting on CareerOneStop → ID: d18d688105cd

Senior Data Scientist

Graybar · Saint Louis, MO

Senior

2026-05-07

MO 2026-05-07

View full posting on CareerOneStop → ID: 6abcd3eb1f25

Senior Data Scientist

Graybar · Clayton, MO

Senior

2026-05-07

MO 2026-05-07

View full posting on CareerOneStop → ID: 071c7d3e420a

Senior Data Scientist

Graybar · Chesterfield, MO

Senior

2026-05-07

MO 2026-05-07

View full posting on CareerOneStop → ID: 28dea09f85b4

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Rogers, AR

Manager

2026-05-07

AR 2026-05-07

View full posting on CareerOneStop → ID: 1254779aeb62

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Little Rock, AR

Manager

2026-05-07

AR 2026-05-07

View full posting on CareerOneStop → ID: eb2ba6e053cd

Staff, Data Scientist

Walmart · Bentonville, AR

Senior

2026-05-07

AR 2026-05-07

View full posting on CareerOneStop → ID: 0a317f353efe

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · New Orleans, LA

Manager

2026-05-07

LA 2026-05-07

View full posting on CareerOneStop → ID: 461153f1a368

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Baton Rouge, LA

Manager

2026-05-07

LA 2026-05-07

View full posting on CareerOneStop → ID: 60c555056e6b

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Madison, WI

Manager

2026-05-07

WI 2026-05-07

View full posting on CareerOneStop → ID: bb8133a7f334

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Milwaukee, WI

Manager

2026-05-07

WI 2026-05-07

View full posting on CareerOneStop → ID: d569510d3bc5

R&D Senior Manager - Data Science

Amcor · Neenah, WI

Manager

2026-05-07

WI 2026-05-07

View full posting on CareerOneStop → ID: 71e85b95eff3

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Chicago, IL

Manager

2026-05-07

IL 2026-05-07

View full posting on CareerOneStop → ID: 154c84de7067

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Springfield, IL

Manager

2026-05-07

IL 2026-05-07

View full posting on CareerOneStop → ID: 294e866751c0

Business Operations Manager - Machine Learning and AI

JPMorgan Chase · Chicago, IL

Manager

2026-05-07

IL 2026-05-07

View full posting on CareerOneStop → ID: dc75cfe2234f

Data Scientist / Portfolio Risk Manager

BMO Financial Group · Chicago, IL

Manager

2026-05-07

IL 2026-05-07

View full posting on CareerOneStop → ID: 1f61d7aa1149

INTL - Remote Sr. Machine Learning Systems Engineer - LATAM

Insight Global · Chicago, IL

Senior

2026-05-07

IL 2026-05-07

View full posting on CareerOneStop → ID: d9a540cca837

Lead Machine Learning Engineer

Capital One · Chicago, IL

Senior

2026-05-07

IL 2026-05-07

View full posting on CareerOneStop → ID: be7a33772138

Senior AI Machine Learning Engineer

The Hartford · Chicago, IL

Senior

2026-05-07

IL 2026-05-07

View full posting on CareerOneStop → ID: a0065b5180c6

Senior Data Scientist, Emerging Technology and Innovation

The Hartford · Chicago, IL

Senior

2026-05-07

IL 2026-05-07

View full posting on CareerOneStop → ID: c294a62a6183

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Birmingham, AL

Manager

2026-05-07

AL 2026-05-07

View full posting on CareerOneStop → ID: 183110f78e37

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Montgomery, AL

Manager

2026-05-07

AL 2026-05-07

View full posting on CareerOneStop → ID: f2b17a85cd65

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Huntsville, AL

Manager

2026-05-07

AL 2026-05-07

View full posting on CareerOneStop → ID: a0b76d6fbbe1

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Chattanooga, TN

Manager

2026-05-07

TN 2026-05-07

View full posting on CareerOneStop → ID: 3a476aa91531

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Memphis, TN

Manager

2026-05-07

TN 2026-05-07

View full posting on CareerOneStop → ID: 749d09bba52f

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Nashville, TN

Manager

2026-05-07

TN 2026-05-07

View full posting on CareerOneStop → ID: 874834a87f72

data scientist, Data & Analytics (Nashville, TN)

Starbucks · Nashville, TN

Mid-level

2026-05-07

TN 2026-05-07

View full posting on CareerOneStop → ID: d10d1a6b94ad

Senior/Lead Data Scientist, Data & Analytics (Nashville, TN)

Starbucks · Nashville, TN

Senior

2026-05-07

TN 2026-05-07

View full posting on CareerOneStop → ID: 39cfd41491b4

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Frankfort, KY

Manager

2026-05-07

KY 2026-05-07

View full posting on CareerOneStop → ID: f25222f8438d

AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY · Louisville, KY

Manager

2026-05-07

KY 2026-05-07

View full posting on CareerOneStop → ID: 6bc808580c4a

ASIC Design Engineer II, Annapurna Labs - Cloud-Scale Machine Learning Acceleration

Amazon · Cupertino, CA

Mid-level

2026-05-07

WA 2026-05-07

View full posting on CareerOneStop → ID: 06e11f5ca079

Data Scientist, AWS Quick Data

Amazon · Santa Clara, CA

Mid-level

2026-05-07

WA 2026-05-07

View full posting on CareerOneStop → ID: f8299709a1eb

Machine Learning Engineer, Sign-Up Flow Optimization

Paramount · West Hollywood, CA

Mid-level

2026-05-07

WA 2026-05-07

View full posting on CareerOneStop → ID: 92c4172d6761

Data Science - Forecasting & Lab, SCOT Forecasting & Lab

Amazon · Bellevue, WA

Mid-level Bachelor's

2026-05-06

WA 2026-05-06

Requirements

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data scientist experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Bachelor's degree
Experience applying theoretical models in an applied environment

Preferred

Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company

Responsibilities

Analysis of large amounts of data from different parts of the supply chain and their associated business functions
Improving upon existing machine learning methodologies by developing new data sources, developing and testing model enhancements, running computational experiments, and fine-tuning model parameters for new models
Formalizing assumptions about how models are expected to behave, creating definitions of outliers, developing methods to systematically identify these outliers, and explaining why they are reasonable or identifying fixes for them
Communicating verbally and in writing to business customers with various levels of technical knowledge, educating them about our research, as well as sharing insights and recommendations
Utilizing code (Python, R, Scala, etc.) for analyzing data and building statistical and machine learning models and algorithms
As a Data Scientist in SCOT, you will be tasked to understand and work with cutting edge research to enable the implementation of sophisticated models on big data. As a successful data scientist in the SCOT team, you are an analytical problem solver who enjoys diving into data from various businesses, is excited about investigations and algorithms, can multi-task, and can credibly interface between scientists, engineers and business stakeholders. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future.

View full posting on CareerOneStop → ID: 7b49a33bff51

Data Scientist

Actalent · Bothell, WA

Mid-level Doctorate

2026-05-06

WA 2026-05-06

Requirements

PMS or equivalent in computational biology, bioinformatics, biostatistics, computer science, genomics or a related field with postdoctoral research experience in Cancer Biology; or MS in cancer biology or related field with established advanced capability and track record in developing and applying computational and bioinformatics methods.
Five years or more of post-PhD academic and/or industry experience working with large, multidimensional, genomics datasets (e.g. NGS, RNA-Seq, transcriptomics, proteomics, flow cytometry, etc.)
Strong foundation in molecular biology and next-generation sequencing technologies (DNA-seq, RNA-seq, targeted panels, WES/WGS)
NGS Data Analysis
Hands-on experience analyzing NGS data end-to-end, including:
o Raw data processing and quality control (FASTQ, BAM/CRAM)
o Alignment, variant calling, and/or expression quantification
o Annotation and interpretation of variants or molecular signatures
Familiarity with common NGS tools and frameworks (e.g., BWA, Bowtie2, GATK, SAMtools, Picard, STAR, Salmon, Kallisto)
Pipeline Development & Automation
Proven experience developing, optimizing, and maintaining reproducible bioinformatics pipelines
Familiarity with workflow management systems (e.g., Nextflow, Snakemake, WDL/Cromwell)
Strong scripting and automation skills in Bash, Python, and R.
Software & Data Engineering
Experience writing code versioned with Git/GitHub
Ability to design modular, scalable, and maintainable analytical workflows
Familiarity with containerization technologies (Docker, Singularity/Apptainer)
Statistical & Computational Skills
Solid understanding of statistics and applied methods relevant to genomics (e.g., differential expression, QC metrics, batch effects)
Experience with data visualization and reporting for scientific and non-scientific audiences
Ability to assess analytical performance, accuracy, and robustness
Computing Environments
Experience working in Linux/Unix environments
Familiarity with high performance computing (HPC) clusters and/or cloud platforms (AWS, GCP, Azure)
Understanding of data storage, data transfer, and compute optimization in large-scale datasets
Experience supporting product development, diagnostics, or translational research in an industry setting
Familiarity with assay validation concepts, analytical performance metrics, and documentation requirements
Exposure to regulated or quality-driven environments (e.g., CLIA, CAP) is a strong plus
Collaboration & Communication
Ability to clearly communicate technical results, assumptions, and limitations to cross functional teams
Experience collaborating with wet lab scientists, software engineers, and program partners
Strong documentation skills for pipelines, analyses, and standard operating procedures

Responsibilities

The Bioinformatics Scientist Contractor will support the Translational Pathology Biomarker Testing Laboratory (TPBTL) within the Translational Medicine department.
The Bioinformatics Scientist applies advanced computational and statistical methods to analyze next generation sequencing (NGS) data to support research, clinical, or translational objectives. This role is responsible for developing, validating, and maintaining scalable, production-ready bioinformatics pipelines
for genomic, transcriptomic, and other high-throughput sequencing applications. Working in a highly collaborative environment, the Bioinformatics Scientist partners closely with wet-lab scientists, pathologists, and bioinformatics team to support data-driven decision-making in both research and CLIA regulated environments.

View full posting on CareerOneStop → ID: 73f2a8b90959

Data Scientist, Advertising, AMPI Measurement

Amazon · Seattle, WA

Mid-level Bachelor's

2026-05-06

WA 2026-05-06

Requirements

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data scientist experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Bachelor's degree
Experience applying theoretical models in an applied environment

Preferred

Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company
Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.

Responsibilities

Translate / Interpret:
Partner with cross-functional teams to translate business questions into rigorous causal inference problems
Design observational studies and quasi-experiments to measure marketing effectiveness when traditional A/B tests are infeasible
Work with data engineering to instrument new data pipelines when existing data cannot answer the causal question
Measure / Quantify / Expand:
Own and evolve production attribution models across multiple marketing channels
Build and maintain causal inference pipelines using methods such as Difference-in-Differences, Synthetic Control, Double Machine Learning, and Media Mix Models
Develop scalable PySpark and Python codebases that process large-scale event data
Continuously improve model accuracy through feature engineering, heterogeneity analysis, and sensitivity testing
Explore / Enlighten:
Investigate anomalies in model outputs and deep-dive to identify root causes
Develop automated data quality checks and model diagnostics
Research and prototype next-generation measurement methods
Make Decisions / Recommendations:
Present findings to senior leadership with clear recommendations
Build dashboards and self-service tools that enable stakeholders to explore results independently
Write production-quality Python code for data analysis, model training, and result publishing

View full posting on CareerOneStop → ID: 21012cb296bf

Machine Learning Engineer III

Indeed · Seattle, WA

Mid-level Doctorate

2026-05-06

WA 2026-05-06

Responsibilities

As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the team, and guide other members of the team to achieve product/technical goals. On a daily basis, you will explore data and formulate problem statements, develop and deploy predictive models while monitoring them in production, and guide the team on the same. Additionally, you will partner with cross-functional teams, evangelize your team's work, and stay updated with the latest advancements in the field.
Partner with cross-functional teams to enhance and optimize search algorithms for improved accuracy, relevance, and overall user experience.
Experiment with Proof of Concept Machine Learning model improvements, scale them to production, and run iterative A/B experiments to improve our matching technology while partnering with other teams
Define and clarify project priorities, deliverables, and success criteria in partnership with cross-functional teams.
Act as a bridge between technical and non-technical collaborators, facilitating effective communication and comprehension of project goals and outcomes.
Mentor and grow other software engineers and Machine Learning Engineers across teams
Break down larger Machine Learning initiatives into pieces that deliver incremental business value and guide the team through implementing them
Represent Indeed at major Machine Learning conferences, such as Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the International Conference on Learning Representations (ICLR).
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
Prior success in deploying impactful Machine Learning solutions to large-scale production systems, while partnering across teams
Solid knowledge of data structures and algorithms
Sense of ownership and accountability as a key contributor in the technical and product domains
Knowledge and practical experience working on Deep Learning Libraries (like Torch, Tensorflow, etc.)
Excellent written and verbal communication in English, effective with technical and business audiences

View full posting on CareerOneStop → ID: f2ee8858280e

Principal Data Scientist

Microsoft Corporation · Redmond, WA

Senior Doctorate

2026-05-06

WA 2026-05-06

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.

Preferred

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) \
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
5+ years of experience in data science modeling, statistics, analytics, business intelligence, or data-driven business strategy.?
Previous?web analytics, product analytics and or content analytics experience.?
Knowledge of Ads and content ecosystem
Interpersonal communication and ability to?leverage?the data to tell a story.?
Demonstrated stakeholder management ability including effective prioritization, clear and concise communication, and delivery of actionable data-driven insights.?
Knowledge on big data processing from raw events to metrics and insights

Responsibilities

Build metrics system to measure Business Health and quick identify the root cause when metrics moves.
Collaborate with cross-functional teams to understand features, estimate impacts and drive the engagement improvements based on insights from big data.
Enhance products by evaluating performance metrics and user feedback. Develop self-service dashboards and reports for various stakeholders using reporting platforms.
Analyze large datasets to?identify?patterns, trends, and content performance to improve the relevance and quality of our recommendation systems.?
Conduct business modeling to identify growth opportunities and initiate projects with a positive long-term ROI.
Design and conducting A/B tests to evaluate algorithm performance and proposing iterative improvements based on the results.?
Effectively communicate findings, insights, and make recommendations to both technical and non-technical stakeholders, enabling informed decision-making.

View full posting on CareerOneStop → ID: e1d6eb689973

Senior Data Scientist - Consumer Marketing

Microsoft Corporation · Redmond, WA

Senior Doctorate

2026-05-06

WA 2026-05-06

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) of industry experience in data science, machine learning, or applied statistics with repeated production impact
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years of industry experience in data science, machine learning, or applied statistics with repeated production impact
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years of industry experience in data science, machine learning, or applied statistics with repeated production impact
OR equivalent experience.

Preferred

High proficiency in Python and SQL with command of large-scale data processing and feature engineering.
Experience building segmentation and personalization systems using large behavioral datasets (including clickstream).
Experience in experimentation, causal inference, and statistical decision frameworks.
Experience leading cross-functional technical initiatives as an individual contributor.
Demonstrated ability to translate complex analyses into executive-level recommendations.
Experience with real-time or near-real-time personalization architectures.
Deep familiarity with LLM engineering practices, including eval harnesses, RAG/grounding patterns, prompt workflows, and model operations.
Experience with synthetic experimentation methods and simulation-based design.
Knowledge of responsible AI, model risk management, and governance in enterprise environments.
Track record of creating reusable platforms/assets that improve organizational velocity.
Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Responsibilities

Define and lead the technical strategy for causal modeling & virtual experimentation approaches (simulation, synthetic controls/data generation where appropriate) to de-risk decisions and accelerate learning.
Collaborate tightly with internal and external partners on the technical strategy for user segmentation at scale, combining clickstream, CRM (customer relationship management), product telemetry, and campaign data to power personalized experiences.
Architect and deliver production-grade personalization models for website and outbound channels (email, push, lifecycle, campaign orchestration).
Lead complex ML (machine learning) efforts from problem framing to deployment, monitoring, drift detection, retraining strategy, and business readouts.
Partner deeply with SME's (subject matter experts) and cross-functional teams to guide LLM (large language model) engineering direction, including model selection, evaluation frameworks, prompt/system design, grounding patterns, and responsible deployment practices.
Establish robust evaluation and governance standards across classical ML and LLM systems (quality, safety, reliability, latency, and cost).
Influence multi-team roadmap and investment decisions through opportunity sizing, forecast modeling, and clear executive communication.
Mentor other individual contributors through technical leadership, design reviews, and reusable patterns that raise the bar across the organization.
Sets technical direction for a significant problem space spanning multiple teams.
Operates autonomously on ambiguous, high-impact initiatives with durable business outcomes.
Creates methods, frameworks, and standards adopted beyond immediate project boundaries.
Acts as a recognized technical leader in both advanced analytics/ML and emerging AI capabilities.

View full posting on CareerOneStop → ID: 5eb8c2f365cd

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Olympia, WA

Director Bachelor's

2026-05-06

WA 2026-05-06

Requirements

Bachelor's degree in data sciences, computer science and 4-6 years of relevant experience

Preferred

Demonstrated experience with scripting and implementing data analytics algorithms and models. Hands on experience using a modeling and simulation software (e.g. Python, Matlab, R, NONMEM, SAS, S-Plus, etc.) is a plus.
Knowledge/Experience in the usage of machine learning/AI tools in life science area(s) and handling life science datasets is preferred.
Excellent interpersonal, technical, and communication skills to lead cross-functional teams.
Profound grasp of Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop.
Have implemented machine learning projects from initiation through completion with particular focus on automated deployment and ensuring optimized performance.
Agile skills and experience
Experience in Healthcare (esp. US) industry is a plus.
*Accountability for Results - Stay focused on key strategic objectives, be accountable for high standards of performance, and take an active role in leading change.
*Strategic Thinking & Problem Solving - Make decisions considering the long-term impact to customers, patients, employees, and the business.
*Patient & Customer Centricity - Maintain an ongoing focus on the needs of our customers and/or key stakeholders.
*Impactful Communication - Communicate with logic, clarity, and respect. Influence at all levels to achieve the best results for Otsuka.
*Respectful Collaboration - Seek and value others' perspectives and strive for diverse partnerships to enhance work toward common goals.
*Empowered Development - Play an active role in professional development as a business imperative.
Minimum $169,222.00 - Maximum $253,000.00, plus incentive opportunity: The range shown represents a typical pay range or starting pay for individuals who are hired in the role to perform in the United States. Other elements may be used to determine actual pay such as the candidate's job experience, specific skills, and comparison to internal incumbents currently in role. Typically, actual pay will be positioned within the established range, rather than at its minimum or maximum. This information is provided to applicants in accordance with states and local laws.

Responsibilities

The Omnichannel Center of Excellence is dedicated to driving innovation, building, and delivering capabilities that enhance Otsuka's opportunity to make an impact in the lives of those we serve. We achieve this through our relentless focus on customer centricity, patient empathy, expertise in enabling pathways for disease education and awareness of management options, and our unwavering commitment to supporting access to treatment.
We are looking for an Omnichannel Data Scientist , Medical Omnichannel with strong expertise in artificial intelligence, encompassing machine learning, data mining, and information retrieval. This position specifically entails the conceptualization, prototyping and development of next generation advanced analytics model-based decision engines and services. The ideal candidate will engage closely with key stakeholders to understand strategic objectives and leverage advanced data analytics and machine learning techniques to enhance communication strategies, ensuring seamless and personalized interactions with healthcare professionals (HCPs) and key opinion leaders (KOLs).
*Data Integration & Management
Explore and analyze common pharmaceuticals data (e.g., claims) as well as novel data sets based on lab and EHR systems. Work with Omnichannel Data Engineer to Integrate data from multiple sources (e.g., CRM systems, social media, email platforms) to create a unified view of stakeholder interactions.
Apply natural language processing (NLP) to extract insights from unstructured medical texts, such as clinical notes or call center transcripts.
Identifying relevant data drivers (features) that can inform decision making closely tied with strategy and creating visualizations to help communicate findings.
*Advanced Analytics & Modeling
Implement advanced analytics models, including predictive analytics and clustering algorithms, to generate actionable insights and track trends across various channels.
Work with Omnichannel ML/Ops engineer to build, test, and deploy production-grade predictive models and algorithms as part of the Omnichannel COE decision engine to meet business needs, including optimization of sales activities and predicting drivers of customer behavior.
Create repeatable, interpretable, dynamic, and scalable models that are seamlessly incorporated into analytic data products and match the needs of Otsuka's growing portfolio.
Collaborate on MLOPS life cycle experience with MLOPS workflows traceability and versioning of datasets. Build and maintain familiarity with Otsuka Machine Learning tech stack including AWS, Kubernetes, Snowflake, and Dataiku
*Omnichannel Optimization
Design and deploy recommendation systems to tailor communications based on stakeholder preferences and behaviors. Utilize machine learning algorithms (e.g., collaborative filtering, content-based filtering) to enhance personalization efforts.
Analyze the performance of omnichannel campaigns (email, SMS, in-app, HCP portals, etc.) to identify high-impact touchpoints and optimize engagement strategies. Use A/B testing and uplift modeling to evaluate the effectiveness of different communication strategies and content types.
*Stakeholder Collaboration
Effectively communicating analytical approach to address strategic objectives to business partners.
Work closely with medical affairs, marketing, and IT teams to ensure alignment and integration of omnichannel strategies. Provide technical guidance and support to cross-functional teams on data-related projects.
Stay updated with emerging industrial trends (Conferences and community engagement) and develop strategic industry partnerships on Omnichannel analytics to strengthen Otsuka's analytical methods and outcomes.
Model Otsuka's core competencies (Accountability for Results, Strategic Thinking & Problem Solving, Patient & Customer Centricity, Impact Communications, Respectful Collaboration & Empowered Development) that define how we work together at Otsuka. Key matrixed partners included: Brand Marketing, Creative / CRM / Digital agencies, Media, Market Research, Analytics, Otsuka Information Technology (OIT), Sales Operations, and Medical/Regulatory/Legal integrated business partners.

View full posting on CareerOneStop → ID: 78775408b027

Machine Learning Engineer III

Indeed · Portland, OR

Mid-level Doctorate

2026-05-06

WA 2026-05-06

Responsibilities

As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the team, and guide other members of the team to achieve product/technical goals. On a daily basis, you will explore data and formulate problem statements, develop and deploy predictive models while monitoring them in production, and guide the team on the same. Additionally, you will partner with cross-functional teams, evangelize your team's work, and stay updated with the latest advancements in the field.
Partner with cross-functional teams to enhance and optimize search algorithms for improved accuracy, relevance, and overall user experience.
Experiment with Proof of Concept Machine Learning model improvements, scale them to production, and run iterative A/B experiments to improve our matching technology while partnering with other teams
Define and clarify project priorities, deliverables, and success criteria in partnership with cross-functional teams.
Act as a bridge between technical and non-technical collaborators, facilitating effective communication and comprehension of project goals and outcomes.
Mentor and grow other software engineers and Machine Learning Engineers across teams
Break down larger Machine Learning initiatives into pieces that deliver incremental business value and guide the team through implementing them
Represent Indeed at major Machine Learning conferences, such as Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the International Conference on Learning Representations (ICLR).
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
Prior success in deploying impactful Machine Learning solutions to large-scale production systems, while partnering across teams
Solid knowledge of data structures and algorithms
Sense of ownership and accountability as a key contributor in the technical and product domains
Knowledge and practical experience working on Deep Learning Libraries (like Torch, Tensorflow, etc.)
Excellent written and verbal communication in English, effective with technical and business audiences

View full posting on CareerOneStop → ID: ea05576560d7

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Boise, ID

Director

2026-05-06

ID 2026-05-06

View full posting on CareerOneStop → ID: 13275226f156

Machine Learning Engineer III

Indeed · Boise, ID

Mid-level

2026-05-06

ID 2026-05-06

View full posting on CareerOneStop → ID: bd4947141ef6

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Salem, OR

Director

2026-05-06

OR 2026-05-06

View full posting on CareerOneStop → ID: 2df07a25fa60

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Helena, MT

Director

2026-05-06

MT 2026-05-06

View full posting on CareerOneStop → ID: 0e4ab639d39c

Machine Learning Engineer III

Indeed · Helena, MT

Mid-level

2026-05-06

MT 2026-05-06

View full posting on CareerOneStop → ID: c29d6adb7163

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Cheyenne, WY

Director

2026-05-06

WY 2026-05-06

View full posting on CareerOneStop → ID: bc136e8100c3

Machine Learning Engineer III

Indeed · Cheyenne, WY

Mid-level

2026-05-06

WY 2026-05-06

View full posting on CareerOneStop → ID: ebc6abb397fe

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Salt Lake City, UT

Director

2026-05-06

UT 2026-05-06

View full posting on CareerOneStop → ID: 9a0d2298f957

Machine Learning Engineer

Extra Space Storage · Salt Lake City, UT

Mid-level

2026-05-06

UT 2026-05-06

View full posting on CareerOneStop → ID: b98af4744e49

Machine Learning Engineer III

Indeed · Salt Lake City, UT

Mid-level

2026-05-06

UT 2026-05-06

View full posting on CareerOneStop → ID: 61931e350b34

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Carson City, NV

Director

2026-05-06

NV 2026-05-06

View full posting on CareerOneStop → ID: cc2f69b57082

Machine Learning Engineer III

Indeed · Las Vegas, NV

Mid-level

2026-05-06

NV 2026-05-06

View full posting on CareerOneStop → ID: 576d7e4724de

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Bismarck, ND

Director

2026-05-06

ND 2026-05-06

View full posting on CareerOneStop → ID: 6a2a8bfde590

Machine Learning Engineer III

Indeed · Bismarck, ND

Mid-level

2026-05-06

ND 2026-05-06

View full posting on CareerOneStop → ID: ef56e765a344

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Pierre, SD

Director

2026-05-06

SD 2026-05-06

View full posting on CareerOneStop → ID: b108bd95b5e1

Machine Learning Engineer III

Indeed · Sioux Falls, SD

Mid-level

2026-05-06

SD 2026-05-06

View full posting on CareerOneStop → ID: 2f33dad3e694

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Phoenix, AZ

Director

2026-05-06

AZ 2026-05-06

View full posting on CareerOneStop → ID: d7d240762a7b

Machine Learning Engineer III

Indeed · Scottsdale, AZ

Mid-level

2026-05-06

AZ 2026-05-06

View full posting on CareerOneStop → ID: c4fa7b874ce5

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Santa Fe, NM

Director

2026-05-06

NM 2026-05-06

View full posting on CareerOneStop → ID: 4486028692d0

Machine Learning Engineer III

Indeed · Albuquerque, NM

Mid-level

2026-05-06

NM 2026-05-06

View full posting on CareerOneStop → ID: ffa8f27b04fe

AI/ML Engineer

Lockheed Martin · Littleton, CO

Mid-level

2026-05-06

CO 2026-05-06

View full posting on CareerOneStop → ID: 3b0bdb83ae36

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Denver, CO

Director

2026-05-06

CO 2026-05-06

View full posting on CareerOneStop → ID: 5b2ec991c1b2

Machine Learning Engineer III

Indeed · Denver, CO

Mid-level

2026-05-06

CO 2026-05-06

View full posting on CareerOneStop → ID: 5cad1787a878

Senior Manager, Innovation Hub Technical Lead - Data Science

Pricewaterhousecoope · Denver, CO

Manager

2026-05-06

CO 2026-05-06

View full posting on CareerOneStop → ID: 41551fefe866

Staff AI/ML Engineer

CACI International · Aurora, CO

Senior

2026-05-06

CO 2026-05-06

View full posting on CareerOneStop → ID: b6657e665fa8

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Lincoln, NE

Director

2026-05-06

NE 2026-05-06

View full posting on CareerOneStop → ID: 5dc0023113db

Machine Learning Engineer III

Indeed · Omaha, NE

Mid-level

2026-05-06

NE 2026-05-06

View full posting on CareerOneStop → ID: 1c51f6285cac

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Topeka, KS

Director

2026-05-06

KS 2026-05-06

View full posting on CareerOneStop → ID: 92e477636518

Machine Learning Engineer III

Indeed · Kansas City, KS

Mid-level

2026-05-06

KS 2026-05-06

View full posting on CareerOneStop → ID: 540a16731d89

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Oklahoma City, OK

Director

2026-05-06

OK 2026-05-06

View full posting on CareerOneStop → ID: 3245d0993356

Machine Learning Engineer III

Indeed · Oklahoma City, OK

Mid-level

2026-05-06

OK 2026-05-06

View full posting on CareerOneStop → ID: d163c9bfab6b

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Saint Paul, MN

Director

2026-05-06

MN 2026-05-06

View full posting on CareerOneStop → ID: 55c3a7c84e98

Machine Learning Engineer III

Indeed · Saint Paul, MN

Mid-level

2026-05-06

MN 2026-05-06

View full posting on CareerOneStop → ID: 9f6f871c89d2

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Des Moines, IA

Director

2026-05-06

IA 2026-05-06

View full posting on CareerOneStop → ID: 1659bff0534b

Machine Learning Engineer III

Indeed · Des Moines, IA

Mid-level

2026-05-06

IA 2026-05-06

View full posting on CareerOneStop → ID: a60ba4f0761a

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Jefferson City, MO

Director

2026-05-06

MO 2026-05-06

View full posting on CareerOneStop → ID: f10722a50915

Machine Learning Engineer III

Indeed · Saint Louis, MO

Mid-level

2026-05-06

MO 2026-05-06

View full posting on CareerOneStop → ID: d2a3d7adc13b

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Little Rock, AR

Director

2026-05-06

AR 2026-05-06

View full posting on CareerOneStop → ID: 3f7d642fb02f

Machine Learning Engineer III

Indeed · Little Rock, AR

Mid-level

2026-05-06

AR 2026-05-06

View full posting on CareerOneStop → ID: 88557049ff17

Senior, Data Scientist - Workforce Intelligence

Walmart · Bentonville, AR

Senior

2026-05-06

AR 2026-05-06

View full posting on CareerOneStop → ID: a966b9d10c14

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Baton Rouge, LA

Director

2026-05-06

LA 2026-05-06

View full posting on CareerOneStop → ID: 7af038678b70

Machine Learning Engineer III

Indeed · Baton Rouge, LA

Mid-level

2026-05-06

LA 2026-05-06

View full posting on CareerOneStop → ID: 223fad402a3b

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Madison, WI

Director

2026-05-06

WI 2026-05-06

View full posting on CareerOneStop → ID: 323784a2f2cd

Machine Learning Engineer III

Indeed · Milwaukee, WI

Mid-level

2026-05-06

WI 2026-05-06

View full posting on CareerOneStop → ID: ba9343f8c33f

Principal Data Scientist (Remote)

EMERGENT HOLDINGS, INC. · New Berlin, WI

Senior

2026-05-06

WI 2026-05-06

View full posting on CareerOneStop → ID: 96be2fefbd93

Senior Data Scientist

CRIBL INC · Madison, WI

Senior

2026-05-06

WI 2026-05-06

View full posting on CareerOneStop → ID: 6789944852d2

Staff Machine Learning Engineer, AI Rese

CRIBL INC · Madison, WI

Senior

2026-05-06

WI 2026-05-06

View full posting on CareerOneStop → ID: 2ae2a2de27fc

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Springfield, IL

Director

2026-05-06

IL 2026-05-06

View full posting on CareerOneStop → ID: fd72f7b87d92

Machine Learning Engineer III

Indeed · Chicago, IL

Mid-level

2026-05-06

IL 2026-05-06

View full posting on CareerOneStop → ID: 24463c171f65

Supply Chain Data Scientist - RadioPharma US & Canada

GE HealthCare · Chicago, IL

Mid-level

2026-05-06

IL 2026-05-06

View full posting on CareerOneStop → ID: de263d79ed4e

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Jackson, MS

Director

2026-05-06

MS 2026-05-06

View full posting on CareerOneStop → ID: ea6c15613275

Machine Learning Engineer III

Indeed · Jackson, MS

Mid-level

2026-05-06

MS 2026-05-06

View full posting on CareerOneStop → ID: b4389d6bb9c0

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Montgomery, AL

Director

2026-05-06

AL 2026-05-06

View full posting on CareerOneStop → ID: b99d4c024e68

Machine Learning Engineer III

Indeed · Huntsville, AL

Mid-level

2026-05-06

AL 2026-05-06

View full posting on CareerOneStop → ID: a6c4b804e707

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Nashville, TN

Director

2026-05-06

TN 2026-05-06

View full posting on CareerOneStop → ID: d364ceb9e6ce

Machine Learning Engineer III

Indeed · Nashville, TN

Mid-level

2026-05-06

TN 2026-05-06

View full posting on CareerOneStop → ID: d8282d429ccb

Associate Director, Medical Omnichannel Data Scientist (Remote)

Otsuka America Pharmaceutical Inc. · Frankfort, KY

Director

2026-05-06

KY 2026-05-06

View full posting on CareerOneStop → ID: 63eae8031378

Machine Learning Engineer III

Indeed · Louisville, KY

Mid-level

2026-05-06

KY 2026-05-06

View full posting on CareerOneStop → ID: f27168bd2b96

Data Scientist II

Applied Materials · Santa Clara, CA

Mid-level

2026-05-06

WA 2026-05-06

View full posting on CareerOneStop → ID: fec16eb0a8bc

Senior Systems Software Engineer, Machine Learning

NVIDIA · Santa Clara, CA

Senior

2026-05-06

WA 2026-05-06

View full posting on CareerOneStop → ID: f3cccf795370

Data Science Consultant

Deloitte · Seattle, WA

Mid-level Master's

2026-05-05

WA 2026-05-05

Requirements

A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates.
At least 2+ years of industry experience outside of academia
Ability to travel 30%, on average, based on the work you do and the client and industries/sectors you serve
Must be legally authorized to work in the United States without the need for employer sponsorship now or at any time in the future

Preferred

A Master's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates.
Good problem decomposition skills and autonomy when faced with solving data problems
Experience manipulating large marketing data sets and performing ETL
Excellent hands-on knowledge of modeling approaches such as Boosted Trees, Logistic regression, Classification Techniques, Unsupervised models, LLM, and experimental design
Experience with large data sets generated in the Ad Tech or Marketing technology spaces
Excellent verbal and written communication skills are required. Candidates must be proficient in conveying complex data insights in an accessible manner to a non-technical audience, including those outside the data science department. This entails adeptness in tailoring messages effectively and choosing appropriate visual aids to facilitate understanding.
Proficiency in high level scripting language, such as Python or R
Understanding of the strategic application of data science methodologies in driving valuable business outcomes for large enterprises
If you have code in the open domain (for example GitHub) or have written about AI/DS please share this with us
Experience with Deep Learning architectures and/or Reinforcement Learning
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $93,000 to $171,300.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

View full posting on CareerOneStop → ID: 8fa5ec90c051

Senior Data Scientist

CRIBL, INC. · Salt Lake City, UT

Senior

2026-05-05

UT 2026-05-05

View full posting on CareerOneStop → ID: 2fcf8e1a9a18

Data Science Consultant

Deloitte · Tempe, AZ

Mid-level

2026-05-05

AZ 2026-05-05

View full posting on CareerOneStop → ID: 15820b0f2b56

Data Science Consultant

Deloitte · Denver, CO

Mid-level

2026-05-05

CO 2026-05-05

View full posting on CareerOneStop → ID: b65fafc760ba

Data Science Consultant

Deloitte · Minneapolis, MN

Mid-level

2026-05-05

MN 2026-05-05

View full posting on CareerOneStop → ID: 9c9720dd7e49

Principal AI Engineer - Advanced AI (Machine Learning, Python, Deep Learning)

Target · Brooklyn Park, MN

Senior

2026-05-05

MN 2026-05-05

View full posting on CareerOneStop → ID: e04a88003ede

Senior Data Scientist - Marketing Analytics

Huntington National Bank · Minnetonka, MN

Senior

2026-05-05

MN 2026-05-05

View full posting on CareerOneStop → ID: ea3a61a71e28

Data Science Consultant

Deloitte · Kansas City, MO

Mid-level

2026-05-05

MO 2026-05-05

View full posting on CareerOneStop → ID: d005f8449789

Data Science Consultant

Deloitte · Saint Louis, MO

Mid-level

2026-05-05

MO 2026-05-05

View full posting on CareerOneStop → ID: 7b95faf52216

Machine Learning Engineers II

Centene Corporation · Clayton, MO

Mid-level

2026-05-05

MO 2026-05-05

View full posting on CareerOneStop → ID: 84d0e0170f82

Director, Data Science

Walmart · Bentonville, AR

Director

2026-05-05

AR 2026-05-05

View full posting on CareerOneStop → ID: d6a808d3fd71

Data Science Consultant

Deloitte · Chicago, IL

Mid-level

2026-05-05

IL 2026-05-05

View full posting on CareerOneStop → ID: 4eb8fc73d873

Manager, Data Scientist - Credit Review

Capital One · Riverwoods, IL

Manager

2026-05-05

IL 2026-05-05

View full posting on CareerOneStop → ID: 911ccd240fcd

Senior Machine Learning Engineer

Capital One · Chicago, IL

Senior

2026-05-05

IL 2026-05-05

View full posting on CareerOneStop → ID: 40ff90463a8a

Principal Data Scientist (Remote)- 14155

Emergent Holdings, Inc. · Corinth, MS

Senior

2026-05-05

MS 2026-05-05

View full posting on CareerOneStop → ID: bef70443ddcd

Senior Data Scientist

Cribl, Inc · Clarksdale, MS

Senior

2026-05-05

MS 2026-05-05

View full posting on CareerOneStop → ID: 00323689878c

Data Science Consultant

Deloitte · Nashville, TN

Mid-level

2026-05-05

TN 2026-05-05

View full posting on CareerOneStop → ID: fa63468ded0d

Senior Data Scientist

Cribl, Inc · Tumwater, WA

Senior

2026-05-04

WA 2026-05-04

B2B SAAS data observability software. Join the company that's building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world's biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructur

View full posting on CareerOneStop → ID: c23451a115ed

Data Scientist II, SCOT OSS - Sourcing Execution & Performance

Amazon · Bellevue, WA

Mid-level Master's

2026-05-02

WA 2026-05-02

Requirements

2+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
2+ years of data querying languages (e.g. SQL, Hadoop/Hive) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Master's degree in a quantitative field, or Bachelor's degree and 5+ years of a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science experience
Experience applying theoretical models in an applied environment

Preferred

Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company

Responsibilities

Collaborate with product managers, science, and engineering teams to design and implement model solutions for Sourcing Execution & Performance systems
Use large datasets or experiments to make causal inferences or predictions
Work with engineers to automate science analysis processes and build scalable measurement solutions
Interpret data, write reports, and make actionable recommendations
Drive technical standards and best practices for the team's Science solutions
Mentor and provide technical guidance to other team members on complex projects
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
Medical, Dental, and Vision Coverage
Maternity and Parental Leave Options
Paid Time Off (PTO)
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!

View full posting on CareerOneStop → ID: 7eca1a38e8a5

Data Scientist, SCOT Forecasting and Labs - CIV Team

Amazon · Bellevue, WA

Mid-level Bachelor's

2026-05-02

WA 2026-05-02

Requirements

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of data scientist experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Bachelor's degree
Experience applying theoretical models in an applied environment

Preferred

Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company

View full posting on CareerOneStop → ID: fec7b9a678c8

Sr. Machine Learning Compiler Engineer, AWS Neuron, Annapurna Labs

Amazon · Seattle, WA

Senior Bachelor's

2026-05-02

WA 2026-05-02

Requirements

5+ years of non-internship professional software development experience
5+ years of programming with at least one software programming language experience
5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Experience as a mentor, tech lead or leading an engineering team

Preferred

Bachelor's degree in computer science or equivalent

View full posting on CareerOneStop → ID: fd03c0af5ae0

Technical Program Manager, MADS - Measurement and Data Science

Amazon · Seattle, WA

Manager

2026-05-02

WA 2026-05-02

Requirements

5+ years of technical product or program management experience
3+ years of software development experience
5+ years of technical program management working directly with software engineering teams experience
Experience managing programs across cross functional teams, building processes and coordinating release schedules
Experience building and evaluating system-level technical design
Experience developing and executing/delivering product and technical roadmaps

Preferred

5+ years of project management disciplines including scope, schedule, budget, quality, along with risk and critical path management experience
Experience defining KPI's/SLA's used to drive multi-million dollar businesses and reporting to senior leadership

Responsibilities

Collaborate with team members to determine and prioritize features and software releases.
Implement mechanisms/tools to provide an accurate view of current feature usage, roadmap and help determine future deliveries.
Collaborate with partners to regularly deep dive on products and drive additional features where necessary.
Drive the implementation and management of Hackathon features so they can be merged into mainline.

View full posting on CareerOneStop → ID: 83af3c8aca76

Data Scientist III - AMZ9971313

IMDB.COM, INC. · Seattle, WA

Mid-level Master's

2026-05-02

WA 2026-05-02

[MULTIPLE POSITIONS AVAILABLE]{.underline} [Employer]{.underline}: IMDB.COM, INC. [Offered Position]{.underline}: Data Scientist III [Job Location]{.underline}: Seattle, Washington [Job Number]{.underline}: AMZ9971313 [

View full posting on CareerOneStop → ID: 41a7dcc4c83f

Machine Learning Engineer, Firefly Services

Adobe Inc. · Seattle, WA

Mid-level Doctorate

2026-05-02

WA 2026-05-02

Requirements

MS or PhD in Computer Science, Machine Learning, or a related field-or equivalent industry experience.
1-3+ years of experience in machine learning, including production-scale deployments.
1-3+ years of experience leading large-scale, GPU-intensive GenAI systems (training, inference, and optimization).
Experience with GenAI frameworks and tools such asPyTorch, CUDA, Triton, TensorRT,Nvidia Dynamo, and Python.
Good understanding of generative model architectures, includingdiffusion models, transformers, and GANs.
Good communication and leadership skills, with a track record of driving alignment in matrixed organizations.

Preferred

Experience withmodel serving, inference, orchestration, and GPU resource managementin large-scale environments.
Hands-on expertise inKubernetes, distributed systems, and MLOps platforms.

Responsibilities

Adobe Firefly'sGenerative AI Servicesteam is seekingSeniorMachine Learning Engineersfor our GenAI Services area. In this high-impact role, you will work with a team of talented engineers in building scalable, high-performance generative AI systems-powering features across Adobe products like Firefly, Photoshop, Illustrator, Express, Stock, and Premiere.You will design and develop efficient inference pipelines, optimize models for latency and through at inference, and build APIs and ecosystems that integrate both Adobe's first-party and third-party generative models into Adobe suite of products that serve individual and enterprise customers. You will tackle Adobe's most complex engineering challenges at the forefront of the the industry, set technical direction, and mentor other ML engineers.Job Responsibilities
Design and evelopmentof core GenAI services and APIs that integrate a wide range of generative models into Adobe's flagship products.
Design and buildML workflows for enterprise-scale model customization, serving, and ecosystem integration.
Collaboratewith Adobe Research and other model developer teams with a focus on model inference strategies and productization of those model
Build and optimizeGPU-accelerated pipelines for both (customized) model training and inference-prioritizing performance, scalability, and reliability.
Foster a culture of innovation, technical excellence, and continuous improvement across the organization.

View full posting on CareerOneStop → ID: 0948b122b9a9

Manager III, Data Science - AMZ9749732

AMAZON WEB SERVICES, INC. · Seattle, WA

Manager Master's

2026-05-02

WA 2026-05-02

[MULTIPLE POSITIONS AVAILABLE]{.underline} [Employer]{.underline}: AMAZON WEB SERVICES, INC. [Offered Position]{.underline}: Manager III, Data Science [Job Location]{.underline}: Seattle, Washington [Job Number]{.underline}:

View full posting on CareerOneStop → ID: c3e6703f8053

Senior Machine Learning Engineer

FlightSafety International Inc · Seattle, WA

Senior

2026-05-02

WA 2026-05-02

Responsibilities

We are looking for a Senior Machine Learning Engineer to redefine how we operate our global services. You won't just be building dashboards; you will be building the "brain" of our infrastructure.
We are moving beyond simple anomaly detection. We are building a self-healing ecosystem where Multi-Agent Systems and Reinforcement Learning (RL) loops work in tandem with Large Language Models (LLMs) to not only detect incidents in real-time but to troubleshoot and resolve them autonomously.
If you are passionate about applying complex AI architectures to massive datasets (billions of telemetry points) to solve real-world reliability challenges, this is the role for you.
This position is an individual contributor role reporting to the Sr. Director, Software Engineering.
*Responsibility
Design and implement autonomous multi-agent systems using Reinforcement Learning (RL) loops that can interact with our infrastructure to perform safe, automated remediation actions
Build GenAI agents capable of digesting logs, traces, and metrics to provide "Human-in-the-loop" root cause analysis and conversational debugging for our SREs
Develop and deploy deep learning models (Transformers, LSTMs, etc.) for forecasting and anomaly detection on high-cardinality, high-volume time series data
Optimize inference pipelines to run with low latency on streaming telemetry data (Kafka/Flink), ensuring we catch issues the moment they happen
Own the lifecycle of your models-from feature engineering on petabyte-scale datasets to training, deployment, and monitoring in production Kubernetes environments
Collaborate with Applied Scientists to translate bleeding-edge research (e.g., causal inference, decision transformers) into production-hardened AIOps tools
Job Designation
*Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation)

View full posting on CareerOneStop → ID: 29961fdcaeeb

Staff Machine Learning Engineer, AI Research

CRIBL, INC. · Salt Lake City, UT

Senior

2026-05-02

UT 2026-05-02

View full posting on CareerOneStop → ID: 6b8951a00d6a

Staff Machine Learning Engineer, AI Researcher

CRIBL, INC. · Salt Lake City, UT

Senior

2026-05-02

UT 2026-05-02

View full posting on CareerOneStop → ID: 30f311c5f2cb

Data Scientist

Vail Resorts · Broomfield, CO

Mid-level

2026-05-02

CO 2026-05-02

View full posting on CareerOneStop → ID: bb2dbcd00f34

DATA SCIENTIST PRINCIPAL, FCH - ENTERPRI

FROEDTERT · Menomonee Falls, WI

Senior

2026-05-02

WI 2026-05-02

View full posting on CareerOneStop → ID: 2a0d7bac8206

Senior Data Scientist

CRIBL INC · Madison, WI

Senior

2026-05-02

WI 2026-05-02

View full posting on CareerOneStop → ID: 1b2c0807230a

Senior IBM AI/ML Engineer

ManpowerGroup · Milwaukee, WI

Senior

2026-05-02

WI 2026-05-02

View full posting on CareerOneStop → ID: 128ff36ea799

Senior Data Scientist

Cribl, Inc · Frankfort, KY

Senior

2026-05-02

KY 2026-05-02

View full posting on CareerOneStop → ID: 580bc42989af

Actuary, Data Science, Global Risk Management &Claims

Amazon · Seattle, WA

Manager Bachelor's

2026-05-01

WA 2026-05-01

Requirements

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data scientist experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Bachelor's degree
Experience applying theoretical models in an applied environment

Preferred

Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company

Responsibilities

? Collaborate with risk management and claims team to identify insurance gaps, propose solutions, and measure impacts insurance brings to the business
? Develop models for new and existing insurance programs utilizing actuarial and data science techniques in innovative ways
? Build forecasts and analyses for businesses under rapid growth, including trend studies, loss distribution analysis, ILF development, and industry benchmarks
? Create processes to monitor loss cost and trends
? Propose and implement loss prevention initiatives with impact on insurance costs in mind
? Advise underwriting decisions with analysis on exposure risk profile
? Support insurance cost budgeting activities
? Collaborate with external vendors and other internal science teams to extract insurance insight
? Conduct other ad hoc analyses and risk modeling as needed

View full posting on CareerOneStop → ID: ea009793ed95

Associate Data Scientist

Carnival Cruise Line · Seattle, WA

Entry-level Master's

2026-05-01

WA 2026-05-01

Requirements

Bachelor's or Master's degree in Mathematics, Statistics, Operations Research, Data Science, or a related numeric discipline.
Experience (internship or 0-2 years) in a data science, analytics, or quantitative modeling role (travel or revenue management industry experience a plus).
Technical proficiency in Python or R, and SQL/relational databases.
Familiarity with forecasting, optimization, and statistical modeling techniques.
Strong communication and interpersonal skills, with the ability to explain complex concepts to non-technical audiences.
Professionalism, reliability, and a collaborative approach to teamwork
At least 2 years experience in a data scientist role, preferably within the travel industry
Experience within Revenue Management
Experience in Systems development a plus, with technical expertise in R or Python, and SQL / relational databases
Travel: No or very little travel likely
Work Conditions: Work primarily in a climate-controlled environment with minimal safety/health hazard potential.
Physical Demands: Must be able to remain in a stationary position at a desk and/or computer for extended periods of time.
This position is classified as "in-office." As an in-office role, it requires employees to work from Holland America's office in Seattle Monday through Thursday each week.
*What You Can Expect
Cruise and Travel Privileges for You and Your Family
Health Benefits
Employee Stock Purchase Plan
Training & Professional Development
Tuition & Professional Certification Reimbursement
Base Hourly Range: $28.46 to $38.41. The range is applicable for the labor market where the role is intended to be hired. Final base salary is directly related to each candidate's qualifications and experience uniquely.

Responsibilities

Holland America Line has been exploring the world since 1873. Our ships offer innovative features and enriching experiences focused on destination exploration and personalized travel, inviting guests to savor the journey.
The Associate Data Scientist will play a hands-on role in supporting the ongoing development, enhancement, and adoption of YODA-the proprietary yield optimization and demand analytics platform built and owned by the data science teams across Carnival Corporation. You will work closely with the Revenue Management (RM) teams across Holland America Line and Seabourn, ensuring YODA's models and analytics are accurate, accessible, and actionable for end users. Your work will help RM teams make better, data-driven decisions and maximize net revenue and profitability.
Here's a summary of what Holland America Line is looking for. Is this you?
Serve as a primary point of contact for RM teams, providing day-to-day support, troubleshooting, and guidance on YODA's features and outputs.
Scope and Develop models as appropriate to support day-to-day pricing and inventory decisions and operations. Help interpret model outputs and analytics for non-technical stakeholders, supporting improved price and inventory decisions.
Gather feedback from end users, translate business questions into analytical tasks, and ensure YODA's tools are well understood and effectively adopted.
Assist in building, validating, and updating forecasting and optimization models within YODA, including price elasticity, booking materialization, cancellation/retention, constraining, and segmentation models. Communicate model updates and implications clearly to RM teams, ensuring transparency and trust in the analytics.
Work closely with the Revenue Science Manager, BI, and ML Ops teams to feed advanced analytics into YODA and associated reporting/alerting systems.
Recommend and help implement enhancements to YODA's toolset and functionality based on user feedback and business needs.
Own YODA release testing for the brands, ensuring all models and changes applied work for the RM teams.
Maintain clear, user-friendly documentation and training materials for YODA.
Support the onboarding and upskilling of RM team members, helping them build confidence and proficiency in using advanced analytics tools.
*Knowledge & Skills:
Scope: Supports the ongoing development, enhancement, and user adoption of the YODA revenue management analytics platform, working directly with Revenue Management teams across Holland America Line and Seabourn to ensure all models and tools are accurate, accessible, and actionable.
Problem solving: Translates business questions and operational challenges from RM teams into analytical tasks, troubleshooting model outputs, and adapting forecasting and optimization approaches to meet evolving commercial needs.
Impact: Enables data-driven, timely, and profitable pricing and inventory decisions by ensuring YODA delivers reliable forecasts and insights, directly supporting the commercial success of both brands. The Junior Data Scientist will materially improve the accuracy and adoption levels of YODA and work with the Revenue Science Manager to ensure YODA continues to develop to meet the evolving needs of the brands
Leadership: Demonstrates initiative by proactively engaging with end users, sharing knowledge, and helping to build analytical capability within the RM teams through clear communication, training, and collaborative problem solving.

View full posting on CareerOneStop → ID: 65a484c016ed

Data Scientist, SPX AI Lab, SPX Science

Amazon · Seattle, WA

Mid-level Master's

2026-05-01

WA 2026-05-01

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of working with or evaluating AI systems experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Preferred

Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

Own the product vision, strategy, and roadmap for a key Seller Assistant capability area.
Define and ship agentic experiences - reasoning, planning, memory, context engineering - that solve hard seller problems at scale.
Partner with scientists and engineers to translate frontier AI research into production-grade features sellers trust and depend on.
Design rigorous evaluation frameworks - automated and human-in-the-loop - to measure agent quality, accuracy, and business impact.
Deep-dive into seller data, identify unmet needs, and write compelling PRFAQs that set the direction for your team.
Drive cross-functional alignment across science, engineering, UX, and business teams to deliver with speed and quality.

View full posting on CareerOneStop → ID: afc613081312

Principal Data Scientist, Prime Video

Amazon · Seattle, WA

Senior Master's

2026-05-01

WA 2026-05-01

Requirements

Bachelors' degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field
11+ years of data scientist experience
Competency in data querying languages (e.g. SQL) and scripting languages (e.g. Python)
Experience with statistical models (e.g., logistic regression. supervised learning approaches)
Experience with online experimentation systems

Preferred

Masters Degree in Data Science or related field
Experience designing and building large-scale online measurement systems
Experience establishing Bayesian decision frameworks for business decisions
Excellent communications with non-technical executive audiences

Responsibilities

Define and drive the multi-year vision for experiment-based measurement systems within Prime Video
Partner with product stakeholders and science peers to identify strategic data-driven opportunities to improve the customer experience
Communicate findings, conclusions, and recommendations to technical and non-technical business leaders across Prime Video
Educate senior leaders about and advocate for high-quality measurement as an input to data-driven decisions
Mentor junior scientists and review technical artifacts to ensure quality
Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organization

View full posting on CareerOneStop → ID: a9d20ec7f26c

Principal Product Mgr Tech, Measurement Ad Tech Data Science (MADS)

Amazon · Seattle, WA

Senior Bachelor's

2026-05-01

WA 2026-05-01

Requirements

2+ years of end to end product delivery experience
8+ years of technical product or program management experience
Bachelor's degree
Experience with feature delivery and tradeoffs of a product
Experience owning/driving roadmap strategy and definition
Experience leading engineering discussions around technology decisions and strategy related to a product
Experience technical product management

Preferred

Experience working directly with Engineers on product enhancements
Experience in project management methodologies, business analysis, or process improvement

View full posting on CareerOneStop → ID: 49c1e394e701

Sr. Data Scientist, Field Engineering

Amazon · Bellevue, WA

Senior Master's

2026-05-01

WA 2026-05-01

Requirements

5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
4+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
Master's degree in a quantitative field such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Engineering, or Computer Science; OR Bachelor's degree and 8+ years of professional experience in a quantitative role.

Preferred

2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
Experience documenting modeling for technical and business leaders
Experience working with data engineers and business intelligence engineers collaboratively
Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)
Experience developing operational processes and data insights
Experience with anomaly detection, predictive maintenance, or reliability modeling in industrial or infrastructure contexts.

Responsibilities

Develop and maintain scalable models and analytical frameworks to measure and predict data center fleet performance, including availability, efficiency, and reliability KPIs across the global AWS infrastructure portfolio.
Apply advanced statistical and machine learning techniques to extract actionable insights from complex, large-scale operational datasets generated by data center systems (power, cooling, controls, etc.).
Partner with Field Engineers, Operations, and Portfolio Managers to identify high-impact opportunities for capacity and availability improvement, translating engineering domain knowledge into quantitative problem formulations.
Design and implement end-to-end data science workflows - from data acquisition and cleaning through model development, validation, and production deployment - enabling repeatable, scalable analysis.
Formalize assumptions about how data center systems are expected to perform and develop methods to systematically identify deviations, root causes, and high-ROI improvement opportunities.
Build self-service datasets, dashboards, and reporting mechanisms that provide Field Engineering leadership with real-time visibility into fleet health and portfolio performance.
Prepare narratives and data-driven recommendations for executive leadership that articulate decision points relative to fleet investment, risk trade-offs, and strategic priorities.
Collaborate with applied science, software engineering, and data engineering teams to ensure models integrate seamlessly with upstream and downstream systems.

View full posting on CareerOneStop → ID: 5532d33a9fd0

Sr. Data Scientist, Field Engineering

Amazon · Seattle, WA

Senior Master's

2026-05-01

WA 2026-05-01

Requirements

5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
4+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
Master's degree in a quantitative field such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Engineering, or Computer Science; OR Bachelor's degree and 8+ years of professional experience in a quantitative role.

Preferred

2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
Experience documenting modeling for technical and business leaders
Experience working with data engineers and business intelligence engineers collaboratively
Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)
Experience developing operational processes and data insights
Experience with anomaly detection, predictive maintenance, or reliability modeling in industrial or infrastructure contexts.

Responsibilities

Develop and maintain scalable models and analytical frameworks to measure and predict data center fleet performance, including availability, efficiency, and reliability KPIs across the global AWS infrastructure portfolio.
Apply advanced statistical and machine learning techniques to extract actionable insights from complex, large-scale operational datasets generated by data center systems (power, cooling, controls, etc.).
Partner with Field Engineers, Operations, and Portfolio Managers to identify high-impact opportunities for capacity and availability improvement, translating engineering domain knowledge into quantitative problem formulations.
Design and implement end-to-end data science workflows - from data acquisition and cleaning through model development, validation, and production deployment - enabling repeatable, scalable analysis.
Formalize assumptions about how data center systems are expected to perform and develop methods to systematically identify deviations, root causes, and high-ROI improvement opportunities.
Build self-service datasets, dashboards, and reporting mechanisms that provide Field Engineering leadership with real-time visibility into fleet health and portfolio performance.
Prepare narratives and data-driven recommendations for executive leadership that articulate decision points relative to fleet investment, risk trade-offs, and strategic priorities.
Collaborate with applied science, software engineering, and data engineering teams to ensure models integrate seamlessly with upstream and downstream systems.

View full posting on CareerOneStop → ID: 7df92be0b7af

Staff Machine Learning Engineer, Search & Knowledge Platform

Apple · Seattle, WA

Senior Doctorate

2026-05-01

WA 2026-05-01

Requirements

MS in Computer Science or related field
10+ years of work experience in machine learning, deep learning or related field
10+ years experience in shipping Search and Q&A technologies and ML systems
Excellent programming skills in mainstream programming languages such as C++, Python, Scala, and Go
Experience delivering tooling and frameworks to evaluate individual components and end-to-end quality
Strong analytical skills to systematically identify opportunities to improve search relevance and answer accuracy
Strong written and verbal communication with the ability to articulate complex topics
Excellent interpersonal skills and teamwork; demonstrated ability to connect and collaborate with others
Passion for building phenomenal products and curiosity to learn

Preferred

PhD in Computer Science, Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or related field
Strong industry background and experience in search and related technologies (LLMs, Machine Learning, NLP, Information Retrieval, Question Answering)
Strong and validated experience of ML development and production systems
Experience working with foundation models and LLMs

Responsibilities

Apple is where individual imaginations come together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us strengthening each other's ideas. That happens because every one of us believes that we can make something wonderful and share it with the world, changing lives for the better! Here, you'll do more than join something - you'll add something.
The Information Intelligence team is redefining how billions of people use their devices to get information. We are an Applied ML team pushing the limits of question answering, assistant response ranking, and search technologies, while also responsible for a production service. We are part of a wider effort to power information across a variety of Apple products - including Siri, Spotlight, Safari, Messages, Lookup, and more.
As a Staff Machine Learning Engineer, you play a critical role in developing world-class Search and Q&A experiences for Apple customers with cutting-edge search technologies and large language models.
As a member of our fast-paced group, you'll have the unique and rewarding opportunity to shape upcoming products from Apple. Our team includes a diversity of backgrounds from applied scientists with a focus in NLP to experienced distributed systems engineers. As such, we are looking for candidates with in-depth understanding of machine learning fundamentals, applied machine learning experience, and strong software engineering skills.
Our team is responsible for delivering next-generation Search and Question Answering systems across Apple products including Siri, Safari, Spotlight, and more. This is your chance to shape how people get information by leveraging your Search and applied machine learning expertise along with robust software engineering skills. You will collaborate with outstanding Search and AI engineers on large scale machine learning to improve Query Understanding, Retrieval, and Ranking, developing fundamental building blocks needed for AI powered experiences such as fine-tuning and reinforcement learning. This involves pushing the boundaries on document retrieval and ranking, developing sophisticated machine learning models, using embeddings and deep learning to understand the quality of matches. It also includes online learning to react quickly to change and natural language processing to understand queries. You will work with petabytes of data and combine information from multiple structured and unstructured sources to provide the best results and accurate answers to satisfy users' information-seeking needs.
As part of our team, you will be leveraging and improving upon the latest deep learning techniques, such as LLM and RAG, in order to understand queries and user intents, rank documents, and find useful answers to users' questions. Our team is responsible for training, fine-tuning and deploying these models at scale, using the latest advances for online inference optimization. Following is the primary list of responsibilities for an ML engineer in the team:

View full posting on CareerOneStop → ID: 964d5769cf12

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Olympia, WA

Manager Doctorate

2026-05-01

WA 2026-05-01

Requirements

Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 years of experience performing data analytics
A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 5 years of experience performing data analytics
A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
At least 2 years of experience leveraging open source programming languages for large scale data analysis
At least 2 years of experience working with machine learning
At least 2 years of experience utilizing relational databases

Preferred

Ph.D. in Physics, Computer Science, Mathematics, or a related field with a strong focus on quantum information or quantum computing.
At least 7 years of experience in quantum computing research and development.
At least 7 years of experience partnering with quantum hardware developers to implement and evaluate algorithms.
At least 7 years of experience in quantum algorithms (e.g. Shor's algorithm, Grover's algorithm, Variational Quantum Eigensolver (VQE), and Quantum Approximate Optimization Algorithm (QAOA)).
At least 7 years of experience in quantum information theory and quantum computing applied to Machine Learning.
Excellent verbal and written communication skills with the ability to effectively communicate technical advances and strategy to research scientists, engineering teams, senior executives, and non-technical audiences.
Knowledge of advanced quantum hardware and their associated control systems.
Experience with large-scale classical simulation of quantum systems (e.g., with tensor networks or state-vector simulators).
Experience with production-level quantum hardware or cloud-based quantum services.
Worked with datasets or systems involving 100+ qubits.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Capital One is open to hiring a Remote Employee for this opportunity.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Remote (Regardless of Location): $209,000 - $238,500 for Sr Mgr, Data Science
McLean, VA: $229,900 - $262,400 for Sr Mgr, Data Science
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website (https://www.capitalonecareers.com/benefits) . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.

View full posting on CareerOneStop → ID: 9ee44c336ec7

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Olympia, WA

Director Doctorate

2026-05-01

WA 2026-05-01

Requirements

Bachelor's degree in Computer Science, Engineering, or AI plus at least 10 years of experience developing or leading AI and ML algorithms or technologies, or Master's degree plus at least 8 years of experience developing or leading AI and ML algorithms or technologies
At least 5 years of people leadership experience

Preferred

7 years of experience managing and leading an engineering team
8+ years of experience deploying scalable, responsible AI solutions on major cloud platforms (AWS, GCP, Azure)
Master's or PhD in Computer Science or a relevant technical fieldProven expertise designing, implementing, and scaling personalization platforms and recommendation systems across feed personalization, ads ranking, or targeted marketing messaging
Proficiency in Python, Java, C++, or Golang; hands-on experience with ML frameworks (PyTorch, TensorFlow) and orchestration tools (Databricks, Airflow, Kubeflow)
Experience optimizing large-scale training and inference systems for hardware utilization, latency, throughput, and cost
Deep expertise in cloud-native engineering, containerization (Docker, Kubernetes), and automated CI/CD deploymentDeep experience with MLOps, model observability, and production ML lifecycle management
Strong track record building organizations, developing managers and senior engineers, and leading through scale and ambiguityExcellent communication and presentation skills, with the ability to influence senior stakeholders and articulate complex AI concepts clearly
Proven leadership in driving platform strategy, cross-functional execution, and technical direction across a large organization
Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers
*_Capital One will consider sponsoring a new qualified applicant for employment authorization for this position._
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Remote (Regardless of Location): $286,200 - $326,700 for Sr. Dir, Machine Learning Engineering
McLean, VA: $314,800 - $359,300 for Sr. Dir, Machine Learning Engineering
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website (https://www.capitalonecareers.com/benefits) . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.

Responsibilities

Lead and scale a high-performing engineering organization responsible for the Personalization Platform that powers real-time, personalized product experiences and multi-channel targeted user messaging across Capital One products and services.
Define the technical strategy, delivery roadmap, and operating model for a portfolio spanning recommendation systems, ranking, decisioning, GenAI infrastructure, MLOps, and low-latency application-serving systems
Build, develop, and manage engineers and engineering leaders; set a high bar for hiring, performance, talent density, coaching, and succession planning across the organization
Partner cross-functionally with Product, Data Science, Cloud Infrastructure, and Machine Learning Platform teams to align strategy, prioritize investments, and co-develop advanced recommendation systems and algorithms serving Capital One users
Drive the design, buildout, and operation of robust ML infrastructure and pipelines supporting feature extraction, model training, testing, guardrails, evaluation, deployment, and both real-time and batch inference with strong reliability, scalability, and operational rigo
Architect low-latency, event-driven systems for real-time personalization and decisioning based on streaming data, user behavior, and contextual signals
Drive the evolution of MLOps practices through automated, metrics-backed deployment workflows, validation and testing systems, model lifecycle governance, and scalable observability
Guide the adoption of state-of-the-art AI and LLM optimization techniques to improve scalability, cost, latency, throughput, and reliability of large-scale production AI systems
Provide organizational technical and people leadership by influencing architecture, engineering standards, delivery excellence, incident management, and cross-team strategy while mentoring managers, tech leads, and senior engineers.
Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI.
Capital One is open to hiring a Remote Employee for this opportunity.

View full posting on CareerOneStop → ID: 2898be3b6034

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Olympia, WA

Senior Doctorate

2026-05-01

WA 2026-05-01

Requirements

Bachelor's degree
At least 10 years of experience designing and building data-intensive solutions using distributed computing
At least 7 years of experience programming in C, C++, Python, or Scala
At least 4 years of experience with the full ML development lifecycle using modern technology in a business critical setting

Preferred

8+ years of experience deploying scalable, responsible AI solutions on major cloud platforms (AWS, GCP, Azure); Master's or PhD in Computer Science or a relevant technical field.
5+ years of proven expertise in designing, implementing and scaling personalization platform and recommendation systems serving one or more areas of Feed Personalization/Ads Ranking/Targeted Marketing Messaging.
5+ years of strong proficiency in Python, Java, C++, or Golang; hands-on experience with ML frameworks (PyTorch, TensorFlow) and orchestration tools (Databricks, Airflow, Kubeflow).
5+ years of experience developing and applying state-of-the-art techniques for optimizing training and inference systems to improve hardware utilization, latency, throughput, and cost.
5+ years of deep expertise in cloud-native engineering, containerization (Docker, Kubernetes), and automated CI/CD deployment.
Passion for staying on top of the latest AI research and AI systems, and judiciously apply novel techniques in production
Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers
Proven leadership in driving platform strategy, fostering cross-functional collaboration, and influencing technical direction across the company.
*_Capital One will consider sponsoring a new qualified applicant for employment authorization for this position._
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Remote (Regardless of Location): $286,200 - $326,700 for Sr Distinguished Machine Learning Enginee
McLean, VA: $314,800 - $359,300 for Sr Distinguished Machine Learning Enginee
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website (https://www.capitalonecareers.com/benefits) . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.

Responsibilities

Define and drive technical strategy and roadmap for our Personalization Platform that powers real-time, personalized product experiences and multi-channel targeted user messaging across all Capital One products and services.
Partner cross-functionally with Product, Data science, Cloud infrastructure, and Machine learning platform teams to align on and co-develop the advanced recommendation systems and algorithms serving our Capital One users.
Develop and maintain a flexible, scalable rules engine to enable business-driven personalization logic, allowing dynamic configuration of user segmentation, targeting rules, and real-time decisioning while integrating seamlessly with ML-driven recommendations.
Design, build and maintain robust ML infrastructure and pipelines to support end-to-end workflows including feature extraction, model training, testing, guardrails, model evaluation, deployment, and both real-time and batch inference - ensuring high performance, scalability, and reliability.
Architect low-latency, event-driven systems for enabling real-time dynamic personalization and decisioning based on streaming data, user behavior, and contextual signals.
Drive the evolution of MLOps practices by building automated metrics-backed deployment workflows, integration validation and testing systems, and scalable monitoring & observability.
Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
Provide organizational technical leadership to influence architecture, engineering standards, cross-team strategies, mentoring engineers and driving organization wide platform innovation.
*The Ideal Candidate:
You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.
Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.
You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.
You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.
Capital One is open to hiring a Remote Employee for this opportunity

View full posting on CareerOneStop → ID: 564c05410bd7

Staff Machine Learning Engineer, AI Research

Cribl, Inc · Tumwater, WA

Senior

2026-05-01

WA 2026-05-01

B2B SAAS data observability software. Join the company that's building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world's biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructur

View full posting on CareerOneStop → ID: 1e6293666c7f

Machine Learning Engineer (multiple openings)

ADOBE SYSTEMS INC · Seattle, WA

Mid-level Master's

2026-05-01

WA 2026-05-01

Use machine language and statistical modeling to evaluate and develop algorithms to improve Adobe products and systems. Duties include: design, develop, and deploy large-scale machine learning systems; architect and develop end-to-end machine learning systems using innovative architectures; develop

View full posting on CareerOneStop → ID: 8335434df4e6

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Boise, ID

Manager

2026-05-01

ID 2026-05-01

View full posting on CareerOneStop → ID: c1fd030d604b

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Boise, ID

Director

2026-05-01

ID 2026-05-01

View full posting on CareerOneStop → ID: 69b130e60af6

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Boise, ID

Senior

2026-05-01

ID 2026-05-01

View full posting on CareerOneStop → ID: be613c0e8cca

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Salem, OR

Manager

2026-05-01

OR 2026-05-01

View full posting on CareerOneStop → ID: af27b0f9b4a0

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Salem, OR

Director

2026-05-01

OR 2026-05-01

View full posting on CareerOneStop → ID: 154859f272f8

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Salem, OR

Senior

2026-05-01

OR 2026-05-01

View full posting on CareerOneStop → ID: 0b34b64f35d1

Senior Data Scientist

Cribl, Inc · Helena, MT

Senior

2026-05-01

MT 2026-05-01

View full posting on CareerOneStop → ID: 6819e9ce3808

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Helena, MT

Manager

2026-05-01

MT 2026-05-01

View full posting on CareerOneStop → ID: 334224b827f1

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Helena, MT

Director

2026-05-01

MT 2026-05-01

View full posting on CareerOneStop → ID: ddba137b44ef

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Helena, MT

Senior

2026-05-01

MT 2026-05-01

View full posting on CareerOneStop → ID: d50b033f228f

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Cheyenne, WY

Manager

2026-05-01

WY 2026-05-01

View full posting on CareerOneStop → ID: 8b6a458d59f1

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Cheyenne, WY

Director

2026-05-01

WY 2026-05-01

View full posting on CareerOneStop → ID: d0518fc67e2d

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Cheyenne, WY

Senior

2026-05-01

WY 2026-05-01

View full posting on CareerOneStop → ID: 1ef9f445854c

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Salt Lake City, UT

Manager

2026-05-01

UT 2026-05-01

View full posting on CareerOneStop → ID: 085cfa0a1545

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Salt Lake City, UT

Director

2026-05-01

UT 2026-05-01

View full posting on CareerOneStop → ID: 7c0652b74b5c

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Salt Lake City, UT

Senior

2026-05-01

UT 2026-05-01

View full posting on CareerOneStop → ID: aeb0828c3299

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Carson City, NV

Manager

2026-05-01

NV 2026-05-01

View full posting on CareerOneStop → ID: 94e6bf3812f2

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Carson City, NV

Director

2026-05-01

NV 2026-05-01

View full posting on CareerOneStop → ID: c6e46367290e

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Carson City, NV

Senior

2026-05-01

NV 2026-05-01

View full posting on CareerOneStop → ID: adc1c445b1e6

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Bismarck, ND

Manager

2026-05-01

ND 2026-05-01

View full posting on CareerOneStop → ID: 58ecc876c6a9

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Bismarck, ND

Director

2026-05-01

ND 2026-05-01

View full posting on CareerOneStop → ID: d1351f6fc9b7

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Bismarck, ND

Senior

2026-05-01

ND 2026-05-01

View full posting on CareerOneStop → ID: 21e99407ae5b

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Pierre, SD

Manager

2026-05-01

SD 2026-05-01

View full posting on CareerOneStop → ID: 3516d69ff7df

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Pierre, SD

Director

2026-05-01

SD 2026-05-01

View full posting on CareerOneStop → ID: ff0166387ae8

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Pierre, SD

Senior

2026-05-01

SD 2026-05-01

View full posting on CareerOneStop → ID: 81c8aea2c492

Data Scientist Lead

PNC · Phoenix, AZ

Senior

2026-05-01

AZ 2026-05-01

View full posting on CareerOneStop → ID: 58b4926cd32c

Data Scientist Sr

PNC · Phoenix, AZ

Senior

2026-05-01

AZ 2026-05-01

View full posting on CareerOneStop → ID: be76f02135db

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Phoenix, AZ

Manager

2026-05-01

AZ 2026-05-01

View full posting on CareerOneStop → ID: a9a1756d8755

Senior Marketing Data Scientist

USAA · Phoenix, AZ

Senior

2026-05-01

AZ 2026-05-01

View full posting on CareerOneStop → ID: c3c3c2481c0e

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Phoenix, AZ

Director

2026-05-01

AZ 2026-05-01

View full posting on CareerOneStop → ID: 5fd260640d6c

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Phoenix, AZ

Senior

2026-05-01

AZ 2026-05-01

View full posting on CareerOneStop → ID: 5a23c8dfd6dd

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Santa Fe, NM

Manager

2026-05-01

NM 2026-05-01

View full posting on CareerOneStop → ID: 1087cb8071fc

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Santa Fe, NM

Director

2026-05-01

NM 2026-05-01

View full posting on CareerOneStop → ID: aa124454b00a

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Santa Fe, NM

Senior

2026-05-01

NM 2026-05-01

View full posting on CareerOneStop → ID: 2eeda3763aa7

Senior Data Scientist

Cribl, Inc · Denver, CO

Senior

2026-05-01

CO 2026-05-01

View full posting on CareerOneStop → ID: 2fc51457cf9f

Senior Data Scientist / AI Machine Learning Research Engineer

CACI International · Denver, CO

Senior

2026-05-01

CO 2026-05-01

View full posting on CareerOneStop → ID: 45fb9acef895

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Denver, CO

Manager

2026-05-01

CO 2026-05-01

View full posting on CareerOneStop → ID: c84d7137cf0b

Senior Marketing Data Scientist

USAA · Colorado Springs, CO

Senior

2026-05-01

CO 2026-05-01

View full posting on CareerOneStop → ID: dc7129c7a1e1

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Denver, CO

Director

2026-05-01

CO 2026-05-01

View full posting on CareerOneStop → ID: 4a0670dfe764

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Denver, CO

Senior

2026-05-01

CO 2026-05-01

View full posting on CareerOneStop → ID: c58e87daf3a5

AI and ML Engineer

BOOZ, ALLEN & HAMILTON, INC. · Offutt A F B, NE

Mid-level

2026-05-01

NE 2026-05-01

View full posting on CareerOneStop → ID: 0d89150ecd84

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Lincoln, NE

Manager

2026-05-01

NE 2026-05-01

View full posting on CareerOneStop → ID: 95d300bbdfa3

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Lincoln, NE

Director

2026-05-01

NE 2026-05-01

View full posting on CareerOneStop → ID: 650aa517546e

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Lincoln, NE

Senior

2026-05-01

NE 2026-05-01

View full posting on CareerOneStop → ID: f6ed51ea5691

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Topeka, KS

Manager

2026-05-01

KS 2026-05-01

View full posting on CareerOneStop → ID: 4dca2b2d54ba

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Topeka, KS

Director

2026-05-01

KS 2026-05-01

View full posting on CareerOneStop → ID: b5b83c980efd

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Topeka, KS

Senior

2026-05-01

KS 2026-05-01

View full posting on CareerOneStop → ID: e7914e1dac35

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Oklahoma City, OK

Manager

2026-05-01

OK 2026-05-01

View full posting on CareerOneStop → ID: 5100e2884ed2

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Oklahoma City, OK

Director

2026-05-01

OK 2026-05-01

View full posting on CareerOneStop → ID: 598c796e4b76

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Oklahoma City, OK

Senior

2026-05-01

OK 2026-05-01

View full posting on CareerOneStop → ID: e477afa85eda

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Saint Paul, MN

Manager

2026-05-01

MN 2026-05-01

View full posting on CareerOneStop → ID: 5506c354d6df

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Saint Paul, MN

Director

2026-05-01

MN 2026-05-01

View full posting on CareerOneStop → ID: e096ba81d544

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Saint Paul, MN

Senior

2026-05-01

MN 2026-05-01

View full posting on CareerOneStop → ID: 511db5346bcb

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Des Moines, IA

Manager

2026-05-01

IA 2026-05-01

View full posting on CareerOneStop → ID: 8e46efefa018

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Des Moines, IA

Director

2026-05-01

IA 2026-05-01

View full posting on CareerOneStop → ID: db445a5950ba

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Des Moines, IA

Senior

2026-05-01

IA 2026-05-01

View full posting on CareerOneStop → ID: 3b8a742ad12d

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Jefferson City, MO

Manager

2026-05-01

MO 2026-05-01

View full posting on CareerOneStop → ID: 891c1423380c

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Jefferson City, MO

Director

2026-05-01

MO 2026-05-01

View full posting on CareerOneStop → ID: 9b9a98e0917e

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Jefferson City, MO

Senior

2026-05-01

MO 2026-05-01

View full posting on CareerOneStop → ID: 6dab19cf33c7

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Little Rock, AR

Manager

2026-05-01

AR 2026-05-01

View full posting on CareerOneStop → ID: 56749da5a207

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Little Rock, AR

Director

2026-05-01

AR 2026-05-01

View full posting on CareerOneStop → ID: f242e3daf551

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Little Rock, AR

Senior

2026-05-01

AR 2026-05-01

View full posting on CareerOneStop → ID: 29775d0571d5

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Baton Rouge, LA

Manager

2026-05-01

LA 2026-05-01

View full posting on CareerOneStop → ID: 967f79861ff1

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Baton Rouge, LA

Director

2026-05-01

LA 2026-05-01

View full posting on CareerOneStop → ID: 9df1e7ffd4ec

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Baton Rouge, LA

Senior

2026-05-01

LA 2026-05-01

View full posting on CareerOneStop → ID: fbb1759e2f3c

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Madison, WI

Manager

2026-05-01

WI 2026-05-01

View full posting on CareerOneStop → ID: ebcd06933b8f

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Madison, WI

Director

2026-05-01

WI 2026-05-01

View full posting on CareerOneStop → ID: 0ad75e10a87d

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Madison, WI

Senior

2026-05-01

WI 2026-05-01

View full posting on CareerOneStop → ID: 1e7d4f0cc5d6

Staff Machine Learning Engineer, AI Rese

CRIBL INC · Madison, WI

Senior

2026-05-01

WI 2026-05-01

View full posting on CareerOneStop → ID: e9cc256bf49d

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Jackson, MS

Manager

2026-05-01

MS 2026-05-01

View full posting on CareerOneStop → ID: 1676512544b3

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Jackson, MS

Director

2026-05-01

MS 2026-05-01

View full posting on CareerOneStop → ID: 2dd19475c4bf

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Jackson, MS

Senior

2026-05-01

MS 2026-05-01

View full posting on CareerOneStop → ID: 79b6d6040385

Staff Machine Learning Engineer, AI Research

Cribl, Inc · Clarksdale, MS

Senior

2026-05-01

MS 2026-05-01

View full posting on CareerOneStop → ID: 22edf28c3f80

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Montgomery, AL

Manager

2026-05-01

AL 2026-05-01

View full posting on CareerOneStop → ID: 8cf2121613a5

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Montgomery, AL

Director

2026-05-01

AL 2026-05-01

View full posting on CareerOneStop → ID: a5c718ded540

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Montgomery, AL

Senior

2026-05-01

AL 2026-05-01

View full posting on CareerOneStop → ID: 86cf74dbcac8

Clinical Data Scientist, Human Capital

Community Health Systems · Franklin, TN

Mid-level

2026-05-01

TN 2026-05-01

View full posting on CareerOneStop → ID: a5fa0a719e55

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Nashville, TN

Manager

2026-05-01

TN 2026-05-01

View full posting on CareerOneStop → ID: 7f891cef27c3

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Nashville, TN

Director

2026-05-01

TN 2026-05-01

View full posting on CareerOneStop → ID: 724de259bd90

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Nashville, TN

Senior

2026-05-01

TN 2026-05-01

View full posting on CareerOneStop → ID: c7fe3c5f1de0

Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)

Capital One · Frankfort, KY

Manager

2026-05-01

KY 2026-05-01

View full posting on CareerOneStop → ID: 8930a868be22

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One · Frankfort, KY

Director

2026-05-01

KY 2026-05-01

View full posting on CareerOneStop → ID: b4a789f1936b

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One · Frankfort, KY

Senior

2026-05-01

KY 2026-05-01

View full posting on CareerOneStop → ID: af68045d0643

Senior Data Scientist - AI Services and Platforms

Highmark Health · Olympia, WA

Senior Doctorate

2026-04-30

WA 2026-04-30

Requirements

2 years Data Science
0 (if PhD Education)
Analysis of business problems/needs
Analytical and Logical Reasoning/Thinking
Collaborative Problem Solving
Data Analysis with SQL, BigQuery
Statistical Analysis with Python, R
Written & Oral Presentation Skills
Basic proto-typing/front end skills ?
*Language (other than English)

Preferred

Ability to stay abreast of the latest research in the field and identify new opportunities for innovation, experiment with new approaches and contribute to the development of novel applications of Generative AI and AI agents.
3+ years of experience with using Python for AI/ML development
Any experience with developing and deploying AI/ML models on AWS Sagemaker, Azure ML, Vertex AI (preferred)
Experience or knowledge in building applications that leverage LLMs as a service, like Vertex AI LLM APIs (Gemini), Azure OpenAI API, Amazon Bedrock, OpenAI API (e.g., GPT-3.5, GPT-4), and/or Anthropic Claude API.
Familiarity with LLM orchestration tools like LangChain, llamaindex for developing RAG based applications.
Experience with designing and implementing end-to-end evaluations of AI/ML solutions, incorporating principles of Responsible AI and building evaluation pipelines
Ability to think creatively and collaborate to apply AI to solve business problems with multiple capabilities, including experience design, change management, and process reengineering.
Excellent communication and presentation skills to explain AI solutions to stakeholders
*LICENSES AND CERTIFICATIONS

Education

Master's Degree in Analytics, Mathematics, Physics, Computer and Information Science, Engineering or closely related field OR Bachelor's degree in Analytics, Mathematics, Physics, Computer and Information Science, Engineering plus 3 years of experience in lieu of Master's degree

Responsibilities

Entirely Remote Work From Anywhere Role!*
We are seeking an experienced data scientist to join our AI Services and Platforms (AIPS) team and drive the development of innovative AI (generative and predictive) based solutions for our enterprise stakeholders. The AIPS team is a critical enabler of AI-driven innovation within the company, functioning as an internal service provider to deliver cutting-edge AI solutions and infrastructure. In this role, you will be instrumental in translating business needs into AI solutions that align with strategic goals and enable long-term success across the organization.
As a Senior Data Scientist , you will leverage your expertise in AI and data to solve diverse business challenges. You will design and build best-in-class AI and agent evaluation capabilities , acting as a technical subject matter expert within cross-functional teams including Business Stakeholders, Data Science, Engineering, Responsible AI & Governance, and Product. You will be essential in laying the foundational R&D work for responsible and scalable AI solutions .
The ideal candidate will have a proven track record of successfully applying Generative AI and Predictive AI to solve complex business problems. This role will play a pivotal role in driving our organization's digital transformation by harnessing the power of Generative AI and data science to extract valuable insights from vast and diverse datasets. We are looking for an individual with a deep understanding of AI techniques , as well as strong data science and problem-solving skills . A successful candidate will have experience with designing and implementing end-to-end evaluations of AI/ML solutions , incorporating principles of Responsible AI and building robust evaluation pipelines. Candidates should also have a strong interest in research and development and be eager to explore new ideas and contribute to the advancement of AI, GenAI, and agentic AI in the healthcare technology space . This role requires a professional dedicated to staying on top of the latest Gen AI research like RAG, fine-tuning, agents, etc. , and is adept at applying them to create innovative products and services. The candidate will also be an excellent communicator , who is able to clearly articulate their findings to business stakeholders.
Work directly with the business to understand their business processes and aims, then identify how analytical solutions could help deliver value for them. This would include being accountable for:
Outlining complex new use cases + creating high level impact estimates
Identifying data elements needed and where to get them (including proxies)
Assembling data sets independently using knowledge of Highmark operational and analytic data structures
Deliver the analytical solution to a complex business problem
Documenting objectives, assumptions and processes in line with our standards
Select and apply the appropriate advanced modeling/machine learning techniques to these data sets to deliver business insight, ensuring that the final analysis is well researched, accurate, and documented. This requires: Experience with a substantial number of advanced analytical techniques and proficiency in a few, evidenced by in-depth knowledge and delivery record (for example regression models, tree-based learning, neural networks, clustering techniques, natural language processing)
Consult with the business to contextualize and translate the results of our analysis in a form which the business can understand and act upon. This will include: Written reports, presentation and data visualizations, and draws clear lines between the high-level problem specifications for colleagues and stakeholders, the analyses performed, and how the results link directly back to business objectives, and work with colleagues to deliver implementation which drives frontline workflow.
Plan, prepare and deliver/coordinate all elements of the analysis at the direction of a manager in such a way that it is delivered on time, to a high standard and ready to implement on a production basis (including dissemination through the Organization's user systems). This includes identifying the best route to implementation (developing the analytical solution accordingly).
Research self- directed new analytical skills and approaches, building relationships internally and externally to transfer knowledge and maintain their position as subject matter experts, consult with fellow data scientists and analysts to guide analysis and deliver larger projects.
Other duties as assigned or requested.

View full posting on CareerOneStop → ID: 3f24a3ae04a7

Senior Machine Learning Engineer, Search & Knowledge Platforms

Apple · Seattle, WA

Senior Bachelor's

2026-04-30

WA 2026-04-30

Requirements

Bachelor's in Computer Science, Machine Learning, or a related field
7+ years of industry or academia experience in machine learning, with a focus on search, NLP, or recommender systems
Strong programming skills in C/C++ or Python, and experience with ML frameworks
Proficient understanding of search algorithms and familiarity with evaluation metrics for search and information retrieval
Excellent communication and collaboration skills

Preferred

Advance degree in Computer Science, Machine Learning, or a related field
5 years of industry or academia experience in machine learning, with a focus on search, NLP, or recommender systems
Familiarity with NLP/ML tools and packages like Jax, TensorFlow, pyTorch, etc.
Experience working with transformer-based models (e.g., BERT, T5) in a search context
Prior industry experience on large scale search systems
Ability to quickly prototype ideas / solutions, perform critical analysis, and use creative approaches for solving complex problems

Responsibilities

Are you passionate about search technologies and building knowledge experiences? The Answers, Knowledge, and Information team is at the forefront of revolutionizing how hundreds of millions of people use their devices to obtain information. We are a world-class team of machine learning engineers who collaborate closely with product, data science, and infrastructure teams to power and enhance features across Apple products, including Siri, Spotlight, Safari, Messages, and more. Our team operates in one of the most dynamic high-performance computing environments, managing petabytes of data and millions of queries per second. As a Senior Machine Learning Engineer, you play a critical role in developing world-class search and Q&A experiences for Apple customers using cutting-edge search technologies and large language models.
As a member of our dynamic team, you will have the unique and rewarding opportunity to contribute to the development of upcoming products from Apple. Our team is responsible for delivering next-generation Search and Question Answering systems across Apple products, including Siri, Safari, Spotlight, and more. Therefore, we are seeking candidates with a deep understanding of large-scale search technology, machine learning fundamentals, applied machine learning experience, and strong software engineering skills. As Senior Machine Learning Engineer for the Search and Knowledge Quality team, you will be responsible for developing the ranking and retrieval technologies that power question answering and search across Apple products. In this role, you will collaborate with world-renowned experts in large-scale data management, machine learning systems, and knowledge extraction, driving advancements in question answering and search, as well as the underlying ranking and retrieval technologies. This is your opportunity to shape how people obtain information by leveraging your Search and applied machine learning expertise, along with robust software engineering skills.

View full posting on CareerOneStop → ID: 574995d5efb4

Senior Data Scientist

Cribl, Inc · Tumwater, WA

Senior

2026-04-30

WA 2026-04-30

B2B SAAS data observability software. Cribl does differently. What does that mean? It means we are a serious company that doesn't take itself too seriously; and we're looking for people who love to get stuff done, and laugh a bit along the way. We're growing rapidly - looking for collaborative,

View full posting on CareerOneStop → ID: 132da146cbe5

Data Scientist I, II

University of Utah · Salt Lake City, UT

Entry-level

2026-04-30

UT 2026-04-30

View full posting on CareerOneStop → ID: f336e25850af

Data Scientist Level lll

Mb Solutions, Inc. · Indian Springs, NV

Mid-level

2026-04-30

NV 2026-04-30

View full posting on CareerOneStop → ID: 17cba48ff872

Sr Data Scientist- Conversational AI & NLU

Citizens · Phoenix, AZ

Senior

2026-04-30

AZ 2026-04-30

View full posting on CareerOneStop → ID: 44652c812fa3

Senior AI/ML Engineer - Remote

UnitedHealth Group · Eden Prairie, MN

Senior

2026-04-30

MN 2026-04-30

View full posting on CareerOneStop → ID: 134e24707322

Senior Data Scientist / Remote

Cribl, Inc · Clarksdale, MS

Senior

2026-04-30

MS 2026-04-30

View full posting on CareerOneStop → ID: 7f8f6c834653

Sr. Specialist, Data Scientist

Butler America · Huntsville, AL

Senior

2026-04-30

AL 2026-04-30

View full posting on CareerOneStop → ID: 8fca0320b5a8

Clinical Data Scientist, Patient Experience

Community Health Systems · Franklin, TN

Mid-level

2026-04-30

TN 2026-04-30

View full posting on CareerOneStop → ID: 6515c9b026bc

Senior Data Scientist - AI Services and Platforms

Highmark Health · Boise, ID

Senior

2026-04-30

ID 2026-04-30

View full posting on CareerOneStop → ID: 13cafe5497e4

Senior Data Scientist - AI Services and Platforms

Highmark Health · Salem, OR

Senior

2026-04-30

OR 2026-04-30

View full posting on CareerOneStop → ID: 77c9032d229b

Machine Learning Engineer, Video Search Team

Apple · Seattle, WA

Mid-level Master's

2026-04-29

WA 2026-04-29

Requirements

4+ years of industry or practical experience in machine learning, NLP, IR, or more recently Large Language Model ( LLMs).
Strong programming skills in Python, Java and Go for building scalable ML systems.
Hands-on expertise in ML libraries such as PyTorch, JAX, TensorFlow for model training and deployment.
Ability to translate product goals into technical solutions, improving user experience.
Strong communication, collaboration, and analytical problem-solving skills.
In-depth knowledge of search and information retrieval fundamentals, including indexing and ranking. Experience with retrieval and ranking algorithms and building big data pipelines using Hadoop, Java, Scala, Spark and more.
Industrial experience in search, classification, recommendation systems, or related fields.
Familiarity with A/B testing and data-driven product development.
Passionate about creating products loved by customers at Apple.
Master's degree or higher (or equivalent practical experience) in Computer Science, Machine Learning, Natural Language Processing, Artificial Intelligence, or a related field.

Preferred

Experience with search or recommendation systems, and semantic retrieval or vector databases.
Expertise in transformer architectures, embeddings, and retrieval or ranking models.
Experience in applying or fine-tuning LLMs for understanding and generation tasks. Familiarity with prompt design, context management, RAG and Agentic architectures and solutions.
Exposure to evaluation and safety frameworks for LLM-based systems.
Knowledge of reinforcement learning and other modern post training practices for LLMs.
Passion for developing intelligent, human-centered experiences to enhance content discovery.

Responsibilities

The Apple Services Engineering AI/ML organization is hiring a Machine Learning Engineer to join the Video Search team.
Our team builds the core intelligence that powers search discovery experiences in the Apple TV App, Siri, and Spotlight cross platforms, helping users effortlessly find and enjoy the content they love. We are a collaborative, high-impact team that values innovation, craftsmanship, and end-to-end ownership from idea to launch. Our systems combine large-scale data, modern retrieval and ranking models, and a deep commitment to user privacy.
Join us, you'll develop scalable systems and machine learning models that drive search relevance, personalization, and understanding of content at scale. Working closely with cross-functional partners in product and design, you'll translate cutting-edge research in advanced machine learning and generative AI into secure and delightful production features used by millions every day.
As a Machine Learning Engineer on the Video Search team, within the Apple Services Engineering AI/ML organization, you will design and deploy large-scale ML systems that power search and discovery across Apple platforms.
You'll apply machine learning, natural language understanding, and generative AI to model user intent and deliver relevant, personalized results. Your work will involve building and optimizing cutting edge data processing, ML models, retrieval pipelines, and ranking systems that operate at global scale and under strict privacy standards.
This is a hands-on role where you will collaborate closely with cross-functional teams to bring advanced ML technologies into production-shaping how users discovery content they love in Apple TV app, cross Apple TV partners on Apple Platforms, also through Siri and Spotlight.

View full posting on CareerOneStop → ID: 455b17ba2d5c

Staff Business Data Scientist, Google Cloud Marketing

Google · Kirkland, WA

Senior Master's

2026-04-29

WA 2026-04-29

Requirements

Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Experience deploying ML models into production environments.

Preferred

9 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Experience with Machine Learning Operations (MLOps) tools and practices.
Understanding of business-to-business (B2B) enterprise SaaS business cycles, demand generation funnels, and marketing technology stacks.

Responsibilities

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.
As a Staff Business Data Scientist, you will serve as a full-stack technical lead, owning the end-to-end life-cycle of data science products that drive Google Cloud's marketing and Go-to-market (GTM) strategy and measurement. You will move beyond traditional analysis to architect and build scalable intelligence systems.
In this role, you will bridge the gap between data engineering and data science. You will build the infrastructure required to ingest and process massive datasets, develop predictive models (e.g., lead scoring, propensity predictions), and engineer the Application Programming Interfaces (APIs) or serving layers that integrate these insights directly into our marketing measurement and tech stack. You will have a specific mandate to leverage Google's Generative AI capabilities and will utilize Large Language Models (LLMs) and Gemini models to engineer novel data science products that enhance our predictive capabilities. You will advocate for software engineering best practices within the data science team, ensuring our code is testable and maintainable. You will work with Marketing leadership to ensure the intelligence systems you build actively influence decision-making. You will also mentor data scientists on the team and advocate for statistical methodology and coding standards across the organization.
The US base salary range for this full-time position is $192,000-$278,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Lead the full Machine Learning (ML) life-cycle from data extraction and feature engineering to model training, validation, and deployment for critical marketing capabilities. Design and build ML models that solve ambiguous business problems and optimize the full customer life-cycle and demand funnel.
Design scalable data science applications using Google's LLM models to unlock insights from structured and unstructured data, build intelligent marketing agents, and automate decision-making processes within the Business-to-Business (B2B) funnel.
Define coding standards and engineering best practices for the team; mentor other data scientists on writing production-quality code and designing scalable architectures.
Partner with engineering and cross-functional data science teams to integrate model outputs directly into our martech systems, ensuring insights drive automated action.
Translate data science outputs into clear, actionable business recommendations for Director and Vice President level stakeholders.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 4c7663329442

Staff Business Data Scientist, Google Cloud Marketing

Google · Seattle, WA

Senior Master's

2026-04-29

WA 2026-04-29

Requirements

Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Experience deploying ML models into production environments.

Preferred

9 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Experience with Machine Learning Operations (MLOps) tools and practices.
Understanding of business-to-business (B2B) enterprise SaaS business cycles, demand generation funnels, and marketing technology stacks.

Responsibilities

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.
As a Staff Business Data Scientist, you will serve as a full-stack technical lead, owning the end-to-end life-cycle of data science products that drive Google Cloud's marketing and Go-to-market (GTM) strategy and measurement. You will move beyond traditional analysis to architect and build scalable intelligence systems.
In this role, you will bridge the gap between data engineering and data science. You will build the infrastructure required to ingest and process massive datasets, develop predictive models (e.g., lead scoring, propensity predictions), and engineer the Application Programming Interfaces (APIs) or serving layers that integrate these insights directly into our marketing measurement and tech stack. You will have a specific mandate to leverage Google's Generative AI capabilities and will utilize Large Language Models (LLMs) and Gemini models to engineer novel data science products that enhance our predictive capabilities. You will advocate for software engineering best practices within the data science team, ensuring our code is testable and maintainable. You will work with Marketing leadership to ensure the intelligence systems you build actively influence decision-making. You will also mentor data scientists on the team and advocate for statistical methodology and coding standards across the organization.
The US base salary range for this full-time position is $192,000-$278,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Lead the full Machine Learning (ML) life-cycle from data extraction and feature engineering to model training, validation, and deployment for critical marketing capabilities. Design and build ML models that solve ambiguous business problems and optimize the full customer life-cycle and demand funnel.
Design scalable data science applications using Google's LLM models to unlock insights from structured and unstructured data, build intelligent marketing agents, and automate decision-making processes within the Business-to-Business (B2B) funnel.
Define coding standards and engineering best practices for the team; mentor other data scientists on writing production-quality code and designing scalable architectures.
Partner with engineering and cross-functional data science teams to integrate model outputs directly into our martech systems, ensuring insights drive automated action.
Translate data science outputs into clear, actionable business recommendations for Director and Vice President level stakeholders.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: e99b5c7a3917

Senior Data Scientist, NLP

Datavant · Olympia, WA

Senior

2026-04-29

WA 2026-04-29

Requirements

We are looking for a motivated Data Scientist to help Datavant revolutionize the healthcare industry with AI. This is a critical role where the right candidate will have the ability to work on a wide range of problems in the healthcare industry with an unparalleled amount of data.
You'll join a team focused on deep medical document understanding, extracting meaning, intent, and structure from unstructured medical and administrative records. Our mission is to build intelligent systems that can reliably interpret complex, messy, and high-stakes healthcare documentation at scale.
This role is a unique blend of applied machine learning, NLP, and product thinking. You'll collaborate closely with cross-functional teams to:
Design and develop models to extract entities, detect intents, and understand document structure
Tackle challenges like long-context reasoning, layout-aware NLP, and ambiguous inputs
Evaluate model performance where ground truth is partial, uncertain, or evolving
Shape the roadmap and success metrics for replacing legacy document processing systems with smarter, scalable solutions
We operate in a high-trust, high-ownership environment where experimentation and shipping value quickly are key. If you're excited by building systems that make healthcare data more usable, accurate, and safe, please reach out.
*What You Will Do
Play a key role in the success of our products by developing models for document understanding tasks.
Perform error analysis, data cleaning, and other related tasks to improve models.
Collaborate with your team by making recommendations for the development roadmap of a capability.
Work with other data scientists and engineers to optimize machine learning models and insert them into end-to-end pipelines.
Understand product use-cases and define key performance metrics for models according to business requirements.
Set up systems for long-term improvement of models and data quality (e.g. active learning, continuous learning systems, etc.).
*What You Need to Succeed
6+ years of experience with data science and machine learning in an industry setting, particularly in designing and building NLP models.
Expertise with Python
Experience with the latest developments in language models (transformers, LLMs, etc.)
Proficiency with standard data analysis toolkits such as SQL, Numpy, Pandas, etc.
Proficiency with deep learning frameworks like PyTorch (preferred) or TensorFlow
Industry experience shepherding ML/AI projects from ideation to delivery
Demonstrated ability to influence company KPIs with AI
Demonstrated ability to navigate ambiguity
*What Helps You Stand Out
Experience with document layout analysis (using vision or multi-modal approaches).
Experience with Spark/PySpark
Experience with Databricks
Experience in the healthcare industry
*After 3 Months, You Will...
Have a strong grasp of technologies upon which our platform is built.
Be fully integrated into ongoing model development efforts with your team.
*After 1 Year, You Will...
Be independent in reading literature and doing research to develop models for new and existing products.
Have ownership over models internally, communicating with product managers, customer success managers, and engineers to make the model and the encompassing product succeed.
Be a subject matter expert on Datavant's models and a source from which other teams can seek information and recommendations.

View full posting on CareerOneStop → ID: a669bed28968

Marketing Data Scientist 4

Bucher & Christian Consulting, Inc. dba BCforward (BCF) · Redmond, WA

Mid-level

2026-04-29

WA 2026-04-29

Requirements

1.Marketing analytics
Databricks is strongly preferred for candidates to have but not required

Responsibilities

We are seeking a Marketing Data Scientist to join our dynamic team. The ideal candidate will have strong experience in marketing analytics, attribution modeling, experimentation, and stakeholder engagement, and a proven ability to translate complex results into clear, actionable recommendations that drive budget decisions and marketing effectiveness.
Measure drivers of player acquisition, reactivation, and long-term value across marketing channels.
Own campaign post-mortems, attribution modeling, and funnel analysis to connect spend and impressions to engagement and monetization outcomes.
Partner with Growth Marketing and Finance to inform budget allocation and build scalable measurement frameworks.
Engage stakeholders through presentations, training, and insight-driven discussions to influence decisions.
Determine data requirements and implement best practices for data manipulation, storage, and analysis strategies.
Design, implement, automate, and maintain large-scale enterprise ETL processes supporting marketing analytics.
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View full posting on CareerOneStop → ID: ccd57eb9e398

Monetization Data Scientist 4

Bucher & Christian Consulting, Inc. dba BCforward (BCF) · Redmond, WA

Mid-level

2026-04-29

WA 2026-04-29

Requirements

Python/Databricks (4+ years)
presentation and communication (5+ years)
attribution and causal inference (4+ years)

Responsibilities

We are seeking a Data Scientist to join our dynamic team supporting a gaming monetization portfolio. The ideal candidate will have strong experience in advanced analytics, experimentation, and predictive modeling in Python and SQL on Databricks and a proven ability to optimize subscription and digital content revenue while protecting player experience.
Apply analytics and experimentation to optimize monetization across subscriptions, marketplace content sales, and creator-driven offerings.
Build LTV and churn propensity models and analyze cross-product spend behavior to inform pricing and packaging.
Design, execute, and interpret A/B tests on pricing, promotions, and UX changes; deliver clear readouts and recommendations.
Partner with Product, Finance, and Marketing to translate business questions into data solutions and influence roadmap decisions.
Design, implement, automate, and maintain scalable ETL pipelines and data models for experimentation and reporting.
Develop logical and physical data definitions and collaborate on database optimization and governance.
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View full posting on CareerOneStop → ID: 4d30096e1673

Senior Data Scientist - Product

Snowflake Inc. · Clyde Hill, WA

Senior Doctorate

2026-04-29

WA 2026-04-29

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don't just use tools; you possess an innate curiosity, treating AI as a high-trust collabora

View full posting on CareerOneStop → ID: d98531b9a121

Sr Data Scientist

T-Mobile USA, Inc · Bellevue, WA

Senior Master's

2026-04-29

WA 2026-04-29

Requirements

4-7 years of industry experience in predictive modeling, data science, and analysis in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models (Required)
4-7 years of experience with data scripting languages (e.g., SQL, Python, R) (Required)
4-7 years of Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data (Required)
4-7 years of experience in data visualization (Required)
4-7 years of experience working with relational database using SQL (Required)
2-4 years of experience with big data architecture and pipeline, Hadoop, Hive, Spark, Kafka, etc. (Required)
2-4 years of experience in the telecom industry preferred
*Knowledge, Skills and Abilities:
Mathematics : Calculus, linear algebra, statistics, and probability
Programming : Expertise in Python and SQL
Machine Learning: Expertise applying machine learning concepts and techniques related to supervised and unsupervised learning
Communication : Strong communication skills, ability to work with cross functional teams
Machine Learning: Expertise applying machine learning concepts and techniques related to supervised and

Education

Bachelor's Degree in Quantitative Discipline (math, statistics, economics, computer science, physics, engineering, etc.) Required
Masters Degree in Quantitative Discipline (math, statistics, economics, computer science, physics, engineering) Preferred.

Responsibilities

Extract, prepare and model large, complex data sets using a combination of skills, including machine learning theory, mathematics, statistics, and programming.
Deliver on-time quality analysis, interpretation, and synthesis of data into effective, concise, and actionable recommendations that enable intelligent decisioning for the company.
Provide senior-level guidance and mentorship to the data science team, including reviewing projects, models, and code for peers and junior team members.
Work with engineering teams to implement and improve machine learning pipelines and production-ready models.
Effectively communicate important information and insights to business leaders using verbal, written, and data visualization skills.
Also responsible for other Duties/Projects as assigned by business management as needed.

View full posting on CareerOneStop → ID: 0e173eaaf7b1

Senior Data Scientist, NLP

Datavant · Boise, ID

Senior

2026-04-29

ID 2026-04-29

View full posting on CareerOneStop → ID: d3c5537ef348

Senior Data Scientist, NLP

Datavant · Salem, OR

Senior

2026-04-29

OR 2026-04-29

View full posting on CareerOneStop → ID: 44cf786499fb

Senior Data Scientist, NLP

Datavant · Helena, MT

Senior

2026-04-29

MT 2026-04-29

View full posting on CareerOneStop → ID: 68ecf5e22983

Senior Data Scientist, NLP

Datavant · Cheyenne, WY

Senior

2026-04-29

WY 2026-04-29

View full posting on CareerOneStop → ID: b08ac76c2ec6

Data Scientist I, II

University of Utah · Salt Lake City, UT

Entry-level

2026-04-29

UT 2026-04-29

View full posting on CareerOneStop → ID: a4a9591120cc

Senior Data Scientist, NLP

Datavant · Salt Lake City, UT

Senior

2026-04-29

UT 2026-04-29

View full posting on CareerOneStop → ID: 26fadfeed96b

Senior Data Scientist, NLP

Datavant · Carson City, NV

Senior

2026-04-29

NV 2026-04-29

View full posting on CareerOneStop → ID: c7edf18c7752

Senior Data Scientist, NLP

Datavant · Bismarck, ND

Senior

2026-04-29

ND 2026-04-29

View full posting on CareerOneStop → ID: 30a929e1850c

Senior Data Scientist, NLP

Datavant · Pierre, SD

Senior

2026-04-29

SD 2026-04-29

View full posting on CareerOneStop → ID: e3b217ccae60

Senior Data Scientist, NLP

Datavant · Phoenix, AZ

Senior

2026-04-29

AZ 2026-04-29

View full posting on CareerOneStop → ID: 3e8c65d3135f

Senior Data Scientist, NLP

Datavant · Santa Fe, NM

Senior

2026-04-29

NM 2026-04-29

View full posting on CareerOneStop → ID: d141495293df

Data Scientist

Booz Allen Hamilton · Aurora, CO

Mid-level

2026-04-29

CO 2026-04-29

View full posting on CareerOneStop → ID: 10b88733d9f2

Data Scientist

Vizient, Inc. · Centennial, CO

Mid-level

2026-04-29

CO 2026-04-29

View full posting on CareerOneStop → ID: 2fd250b23915

Lead Customer Success Data Scientist - Industry Analytics

Cloud Software Group, Inc. · Denver, CO

Senior

2026-04-29

CO 2026-04-29

View full posting on CareerOneStop → ID: a0b10fc0e8d3

Senior Data Scientist, NLP

Datavant · Denver, CO

Senior

2026-04-29

CO 2026-04-29

View full posting on CareerOneStop → ID: 044974e39e29

Senior Data Scientist, NLP

Datavant · Lincoln, NE

Senior

2026-04-29

NE 2026-04-29

View full posting on CareerOneStop → ID: 71d7b9d79365

Senior Data Scientist, NLP

Datavant · Topeka, KS

Senior

2026-04-29

KS 2026-04-29

View full posting on CareerOneStop → ID: 7489775d55fb

Senior Data Scientist, NLP

Datavant · Oklahoma City, OK

Senior

2026-04-29

OK 2026-04-29

View full posting on CareerOneStop → ID: 9dece7ece4a2

Senior Data Scientist, NLP

Datavant · Des Moines, IA

Senior

2026-04-29

IA 2026-04-29

View full posting on CareerOneStop → ID: c105e5766566

Senior Data Scientist, NLP

Datavant · Jefferson City, MO

Senior

2026-04-29

MO 2026-04-29

View full posting on CareerOneStop → ID: 17f6c5effc41

(USA) Senior Manager, Data Science, First Mile Strategy

Walmart · Bentonville, AR

Manager

2026-04-29

AR 2026-04-29

View full posting on CareerOneStop → ID: 21c675a4d729

Senior Data Scientist, NLP

Datavant · Little Rock, AR

Senior

2026-04-29

AR 2026-04-29

View full posting on CareerOneStop → ID: 5f62684f3a9d

Senior Data Scientist, NLP

Datavant · Baton Rouge, LA

Senior

2026-04-29

LA 2026-04-29

View full posting on CareerOneStop → ID: 23b46a89a11a

Senior Data Scientist, NLP

Datavant · Jackson, MS

Senior

2026-04-29

MS 2026-04-29

View full posting on CareerOneStop → ID: 0b0e1ce1288a

Senior Data Scientist, NLP

Datavant · Montgomery, AL

Senior

2026-04-29

AL 2026-04-29

View full posting on CareerOneStop → ID: 219082eb2fa0

Senior Data Scientist, NLP

Datavant · Nashville, TN

Senior

2026-04-29

TN 2026-04-29

View full posting on CareerOneStop → ID: e088d8d763ab

Senior Data Scientist, NLP

Datavant · Frankfort, KY

Senior

2026-04-29

KY 2026-04-29

View full posting on CareerOneStop → ID: b584fca88d44

Data Scientist I, Demand Forecasting

Amazon · Bellevue, WA

Entry-level Bachelor's

2026-04-28

WA 2026-04-28

Requirements

3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
Bachelor's degree
Familiarity with large language models (LLMs) or generative AI applications in analytics or explainability

Preferred

Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
Experience communicating complex ideas to technical and non-technical audiences
Experience with time series forecasting, demand modeling, or bias correction techniques

Responsibilities

Design and analyze experiments (A/B tests) to measure the impact of forecast model changes and SCOT initiatives, drawing causal inferences from both experimental and observational data
Develop bias correction models to improve forecast accuracy across Amazon's demand forecasting systems, including National, Regional, Grocery, SSD, Inbound, and CIV forecasts
Contribute to GenAI/LLM-based research for forecast explainability and interpretability, helping stakeholders understand what drives forecast signals
Support and enhance the Labs experimentation platform by building scalable inference and measurement solutions that quantify the impact of forecasting improvements
Work horizontally across the forecasting product portfolio and collaborate with product managers, applied scientists, and engineering teams to embed analytics and ML solutions where they create the most value
Use large datasets to build models addressing ambiguous forecasting questions, including demand prediction, out of stock, seasonality, and varying lead times and spans
Interpret data, write reports, and communicate measurement results to stakeholders by translating technical frameworks into business-oriented insights and actionable recommendations
Keys to success in this role include exceptional analytics, statistics, judgment, and communication skills. The candidate will need to be able to extract insights from data and clearly communicate appropriate triggers and actions
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
Medical, Dental, and Vision Coverage
Maternity and Parental Leave Options
Paid Time Off (PTO)
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!

View full posting on CareerOneStop → ID: a95faa4943e6

Machine Learning Scientist - Personalization Science, Apple Media Products

Apple · Seattle, WA

Mid-level Doctorate

2026-04-28

WA 2026-04-28

Requirements

6+ years of relevant work experience.
Deep knowledge of machine learning powered personalization algorithms, design patterns and tools. In particular, this includes deep learning, reinforcement learning and unsupervised learning methods.
Knowledge of generative artificial intelligence applied to recommendation systems.
Practical real-world experience with building scalable recommendation systems.
Proven grasp of the open-source Python ML/AI tech stack, including Tensorflow, pytorch, scikit-learn, numpy-scipy-pandas.
Technical competence in production-quality software development.
Familiarity with big data technologies.
Strong written & oral communication skills.
Master's in a quantitative field, including Computer Science, Maths, Statistics, Physics, etc.

Preferred

PhD in a quantitative field, including Computer Science, Maths, Statistics, Physics, etc.

Responsibilities

Wonder how Apple's Media Products show relevant search results and recommendations across Apple's media offerings - including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books? Come join us! Research, design and develop machine learning models that personalize the App Store for billions of users worldwide! Propose, prototype and evaluate algorithm improvements. Build large-scale personalized recommender systems for Apple Music, Apps & Games Recommendations, Video, Podcast and Books Recommendations. See your work touch the lives of billions of Apple users worldwide.
The Apple Services Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books. And we do it on a massive scale, meeting Apple's high expectations with high performance, to deliver a huge variety of entertainment in over 35 languages to more than 150 countries. Our scientists and engineers build secure, end-to-end solutions powered by machine learning. Thanks to Apple's unique integration of hardware, software, and services, designers, scientists and engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, flexible, and multi-functional, offering greater exposure to the array of opportunities here.
We are looking for a world-class researcher to help us solve challenging problems in personalization science using the latest advances in machine learning. With your expertise, we want to develop novel solutions to power personalized experiences across the App Store that enrich the lives of our customers. You will have the incredible opportunity to see your solutions deployed at Apple's truly incredible global scale.

View full posting on CareerOneStop → ID: 9dc66a3f353b

Machine Learning Tools Engineer, SIML

Apple · Seattle, WA

Mid-level Bachelor's

2026-04-28

WA 2026-04-28

Requirements

Bachelor's degree in Computer Science, Engineering, or a related technical field; or equivalent practical experience.
3+ years of experience in software development with strong Python proficiency.
Familiarity with machine learning fundamentals and frameworks (e.g., PyTorch, TensorFlow, JAX).
Experience with Linux systems, containers (Docker), and version control (Git).
Strong debugging, analytical, and problem-solving skills.
Comfortable operating at the intersection of research and product, coordinating across teams with competing timelines and technical constraints.

Preferred

Prior experience in an ML platform, infrastructure, or productivity tools team.
Experience building internal SDKs, CLIs, or automation frameworks for ML or data workflows.
Exposure to distributed training, experiment tracking, or model serving infrastructure.
Experience supporting large internal or external developer communities.

Responsibilities

Are you passionate about Generative AI? Are you interested in working on groundbreaking generative modeling technologies to enrich billions of people? We are the Intelligence System Experience (ISE) team within Apple's software organization. The team operates at the intersection of multimodal machine learning and system experiences. Our multidisciplinary ML teams focus on a broad spectrum of areas, including Visual Generative Foundation Models, Multimodal Understanding, Visual Understanding of People, Text, Handwriting, and Scenes, Personalization, Knowledge Extraction, Conversation Analysis, Behavioral Modeling for Proactive Suggestions, and Privacy-Preserving Learning. These innovations form the foundation of the seamless, intelligent experiences our users enjoy every day.
We are looking for a Machine Learning Tools Engineer to help build and evolve the infrastructure, tools, and libraries that power model development and deployment across our organization. The ideal candidate combines strong software engineering fundamentals with ML domain understanding and a deep passion for improving developer experience. You'll partner closely with researchers, ML engineers, and infra teams to design tools that make training, experimentation, evaluation and inference seamless and efficient. This role is hands-on, user-focused, and requires a balance of building scalable systems and operationally supporting a large and growing user base.
As a Machine Learning Tools Engineer, you will:
Design, develop, and maintain core ML infrastructure components (training pipelines, experiment tracking, deployment tooling, and monitoring systems).
Collaborate with ML practitioners to identify pain points and translate them into productized solutions that enhance productivity and reliability.
Build and maintain Python-based SDKs, CLIs, and APIs that simplify how ML engineers interact with compute, data, and models.
Ensure tools are robust, performant, and user-friendly, with strong observability and documentation.
Partner with infrastructure, MLOps, and platform teams to ensure end-to-end system integration and smooth scaling.
This is a highly collaborative role that requires curiosity, empathy for users, and a drive to make ML development frictionless.

View full posting on CareerOneStop → ID: 226b9e03ca70

Senior Data Scientist

The Boeing Company · Seattle, WA

Senior Bachelor's

2026-04-28

WA 2026-04-28

Requirements

Ability to obtain a US Security Clearance for which the US Government requires US Citizenship
Bachelor's degree or highe
5+ years of experience with AI/ML technologies, frameworks, models and ensembles
5+ years with container and container orchestration (Docker and Kubernetes)
5+ years of experience with data engineering and data pipelines for On-Prem cloud, hybrid data models and data warehouses
5+ years of experience with software programming/scripting (such as Python, Unix/Linux type batch scripting, FORTRAN, C / C++)
This position must meet U.S. export control compliance requirements. To meet U.S. export control compliance requirements, a "U.S. Person" as defined by 22 C.F.R. §120.62 is required.
"U.S. Person" includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asylee.
*Export Control Details:
US based job, US Person required

Preferred

5+ years of experience in the manufacturing or aviation domain
5+ years of experience with big data technologies and data engineering practices
Experience in multi-cloud and hybrid AI architecture
Experience with generative AI, NLP, computer vision, or reinforcement learning
Experience with CI/CD pipelines, DevOps practices and containerized deployments
Experience with open-source ML projects or publications in relevant fields

Responsibilities

At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.
The Boeing Company is currently seeking a Senior Data Scientist to join the Boeing Test & Evaluation (BT&E) Business Operations team in Berkeley, MO or Seattle, WA .
The candidate will lead cross-functional teams to define, build, validate, and deploy advanced predictive and prescriptive analytics solutions that drive measurable business outcomes. This senior individual contributor / technical leader will evaluate business objectives, translate stakeholder needs into analytic requirements, choose appropriate methods and algorithms, perform data preparation and feature engineering, and operationalize models into production systems. The role requires strong domain/business acumen, excellent communication and leadership skills, hands-on modeling experience, and proven success deploying production-grade analytics.
Define the strategy to build highly reliable and scalable ML and AI solutions that align with the organization's business goals and objectives
Lead the creation and implementation of scalable, robust, and high-performance ML architectures including MLOps, AIOps leveraging cloud native services (AWS, Azure, GCP) and open-source frameworks
Design, build, and optimize machine learning models, ensuring accuracy, efficiency, and scalability
Partner with product managers, engineers, and business stakeholders to define problem statements, success metrics, and deployment requirements
Collaborate with data engineers, data architect, software developers, and DevOps teams to integrate ML models into production systems
Assess and recommend ML tools, frameworks, and platforms to deliver business value and foster innovation
Monitor and optimize ML models and systems for latency, throughput, and cost-efficiency in production
Ensure ML systems adhere to ethical guidelines, data privacy regulations, and industry standards
Design and development of Generative AI and AI use cases (LLMs, RAG, Agentic, multi model AI, fine tuning. Vector databases and prompt engineering)
Lead organizational change for the adoption of new platforms, machine learning tools and analytics workflows
Own all communication and collaboration channels pertaining to strategy and assigned projects, including regular stakeholder, senior leadership, and cross-team updates

View full posting on CareerOneStop → ID: 2ec6a541e9db

Senior Machine Learning Engineer - Earner Incentive

Uber · Seattle, WA

Senior Doctorate

2026-04-28

WA 2026-04-28

Requirements

Ph.D., M.S., or Bachelor's degree in Computer Science, Statistics, Mathematics, Machine Learning, Operations Research, or a related field, or equivalent practical experience with demonstrated impact.
5+ years of experience across the end-to-end ML lifecycle, including data analysis, feature engineering, model development, deployment, monitoring, and iteration in large-scale production systems. Proven ability to deliver measurable business impact and strong understanding of MLOps best practices.
Strong understanding of a broad range of ML and statistical techniques, including deep learning (e.g., multi-task learning, transformers), tree-based models, and classical approaches, with solid judgment in selecting methods based on context and data.
Proficiency in at least one production language (Python, Scala, Java, or Go) and common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
Solid software engineering skills, including system design, writing and reviewing production-quality code, testing, and operating ML systems in production.
Strong ownership, learning mindset, collaboration and communication skills; able to work independently and effectively in cross-functional teams.

Preferred

Experience developing and deploying pricing, matching, or incentive algorithms for two-sided marketplaces, with strong product intuition and system-level thinking.
Experience with multi-armed bandits, reinforcement learning, and causal ML, including applying these methods in production systems.
Familiarity with large-scale data and ML infrastructure (e.g. Spark, Flink), and batch or real-time data processing systems.
Strong communication and leadership skills, with the ability to lead initiatives, prototype quickly, drive alignment, and collaborate effectively with cross-functional partners, from early idea generation through productionization.
Experience leading complex technical projects, influencing scope, technical direction, and execution across multiple engineers or teams.
Ability to translate ambiguous business problems into clear, actionable problem statements, define success metrics, and drive execution through well-reasoned trade-offs.
Demonstrated technical leadership, such as mentoring engineers, leading cross-functional efforts, or shaping ML / optimization strategy.
Experience designing, running and analyzing large-scale online experiments to prove impact, interpret results, guide decision-making, and translate insights into concrete product or system changes.
For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Responsibilities

Uber's Marketplace is at the core of the business. The Earner Incentive team in Marketplace builds products and systems that empower drivers through targeted incentives, creating a more balanced and efficient marketplace while enhancing engagement and experience.
The team owns the end-to-end incentive lifecycle, from ML-driven incentive generation to scalable online serving, answering questions such as who, where, when, how, and how much, powered by large-scale machine learning, optimization, and experimentation systems . These systems enable proactive, targeted incentives that shape supply, optimize earnings, and guide marketplace balance.
We are seeking a Senior Machine Learning Engineer to design and scale the technical foundations behind Uber's driver incentive systems. You will develop and productionize large-scale ML models and decision systems that power both scheduled and near real-time, intelligent incentive generation and delivery at Uber's global scale.
In this role, you will collaborate closely with engineers, product managers, operations, and scientists to set technical direction, make thoughtful trade-offs, and turn complex problems into reliable production systems. Your work will directly shape how incentives are designed and delivered at scale, enhancing marketplace efficiency and reliability, and empowering earning opportunities for millions of drivers worldwide.
*What the Candidate Will Do
Design, develop, productionize, and operate end-to-end ML solutions and data pipelines for large-scale systems that power driver incentives.
Develop and apply advanced ML and optimization techniques to design incentive mechanisms for online marketplaces, improving marketplace efficiency and reliability while enabling earning opportunities for millions of drivers.
Build deep domain expertise in incentives, pricing, and marketplace dynamics, and understand how these systems interact with Operations. Translate business requirements into clear problem statements and actionable technical plans, reasoning through trade-offs to deliver practical, production-ready solutions.
Help set the team's technical direction and drive execution in partnership with technical leads. Provide technical mentorship, and review designs and code to maintain high engineering quality.
Collaborate closely with engineers, product managers, scientists, and Operations to drive clarity, alignment, and delivery of high-impact solutions to complex business problems.
Own projects end-to-end, from ideation and design through production rollout and iteration, and drive measurable business impact across teams.

View full posting on CareerOneStop → ID: abd5a070b1c9

Senior Research Data Scientist

The Boeing Company · Seattle, WA

Senior Master's

2026-04-28

WA 2026-04-28

Requirements

Master's degree or higher in a quantitative field such as Data Science, Statistics, Economics, Operations Research, Machine Learning, Engineering, Industrial Organizational Psychology, Organizational Behavior, Psychometrics, Sociology, or a related discipline
5+ years of experience in data science, quantitative research science, or data analytics
5+ years of experience with the following data analytics methods Machine Learning, Simulation, Statistics, Data Mining, Regression, Survival Analysis, Time series models
5+ years of experience in data analysis algorithms (e.g. data mining, statistics, machine learning, natural language processing, text mining, visual analytics) and building Descriptive, Predictive and Prescriptive models
5+ years of experience in database management, programming, statistical modeling and/or machine learning (SQL, R, Python, JMP, Tableau, etc.)
Experience in Business Intelligence/data analytics tools (Microsoft Power BI, Dashboards, SQL, Tableau, etc.)
This is not an Export Control position.

Preferred

10+ years of industry experience
Experience with HR systems and employee data environments
Experience applying AI to automate, accelerate, or optimize analytics, research, or reporting workflows
Experience with employee engagement, culture, leadership, talent, or organizational effectiveness research
Experience applying machine learning models from ideation through monitoring and maintenance
Capability to present highly technical information to nontechnical audiences
Capability to influence senior leaders on strategy, trade-offs, and policy decisions using evidence-based recommendations
Experience applying leading AI techniques and libraries to solve complex business problems and deliver measurable results
Strong visualization skills and experience creating compelling charts, dashboards, and executive summaries
Experience teaching, mentoring, and developing others
*Conflict of Interest:
Successful candidates for this job must satisfy the Company's Conflict of Interest (COI) assessment process.

Education

Master's Degree or Equivalent Required

Responsibilities

At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.
Boeing's Global Talent, Development and Employee Experience organization has an exciting opportunity for a Senior Research Data Scientist to join the Employee Listening, Organizational Research, and Talent Assessment Team in Seattle, WA . The person in this role will lead deep dive analysis of employee survey, assessment, and workforce data, uncover meaningful organizational insights, and translate complex findings into compelling executive level narratives. This role sits at the intersection of research, analytics, strategy, and storytelling, ideal for someone who thrives on turning data into action and influencing senior leaders with clarity and confidence. You will help set the long-term research roadmap, defining measurement frameworks and success metrics, and establish standards for scientific rigor, reproducibility, practical and responsible use of AI/ML.
In this role, you will analyze large and complex datasets from surveys, assessments, HR systems, and business sources to generate actionable insights that inform organizational strategy, talent decisions, and employee experience improvements. You will lead mixed methods research, apply advanced statistical and predictive analytics, and use both structured and unstructured data to identify business trends, drivers, risks, and opportunities.
You will partner with executive leaders, HR, talent, and business teams to frame research questions, synthesize findings, and shape decisions through high impact reporting and storytelling. The ideal candidate combines strong technical expertise with the ability to simplify complex information, influence stakeholders, and help leaders understand the "so what" behind the data.
Lead advanced analysis of organizational survey, assessment, and workforce data to identify trends, drivers, risks, and opportunities
Design and execute research approaches to answer complex business and organizational questions using survey, assessment, interview, and workforce data
Translate ambiguous data into decision-ready executive syntheses, including recommendations, options, trade-offs, risks, and implementation considerations
Develop high-impact executive reports, presentations, and dashboards that tell a compelling data story
Partner with leaders, HR, talent, and business teams to define research questions and inform strategy
Synthesize multiple data sources, including surveys, assessments, open-ended feedback, internal business outcome metrics, and external benchmarks
Apply advanced statistical analysis, machine learning, and predictive modeling to surface insights and forecast outcomes
Advance NLP methods, including sentiment analysis, topic modeling, and entity recognition, to analyze unstructured text data
Conduct qualitative analysis, including coding, thematic analysis, and content analysis, to derive insights from narrative data
Ensure scientific rigor, validity, and reproducibility across all research and analytics through documented methods, version-controlled code, QA checks, and peer review
Present findings to senior stakeholders with confidence, clarity, and influence
Improve research methodologies, reporting standards, and storytelling approaches
Provide technical leadership, guidance, and mentoring to cross-functional partners and teammates
Identify and implement practical AI use cases that streamline workflows, automate repetitive tasks, improve analytical efficiency, and scale research output
Partner with other scientists to build team capability through coaching, documentation, and examples of effective day-to-day AI use

View full posting on CareerOneStop → ID: 3060b2231a4c

Staff Machine Learning Engineer - Rider Intelligence

Uber · Seattle, WA

Senior Doctorate

2026-04-28

WA 2026-04-28

Requirements

Ph.D., M.S. or Bachelor in Computer Science, Mathematics with focus on Machine Learning, or equivalent technical background with exceptional demonstrated impact
8+ years experience leading the development and deployment of ML models in large-scale production environments at top-tier ML companies

Preferred

Expertise in search, recommendation systems, ranking/retrieval, or representation learning is highly desirable.
Proven experience in ranking optimization across heterogeneous content types.
Demonstrated success in leading cross-functional projects that deliver significant business impact.
For Seattle, WA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Responsibilities

Staff Machine Learning Engineers at Uber are passionate and pragmatic technologists who are able to translate business insight and goals into well-formulated ML projects and scalable solutions to deliver impact. They are not only collaborative role models but also approachable leaders, humble teachers while also effective in helping the team in project execution. You will work with talented people in product, science, operations, and platform teams to help build and optimize our Rider Experience products. The role requires technical chops as well as strong communication & leadership skills.
Define and execute technical strategies, spanning from model and system architecture to business objectives and stakeholder alignment.
Lead the design, development, and production of end-to-end ML solutions for large-scale distributed systems serving billions of trips.
Lead and mentor a team of Machine Learning Engineers (MLEs), providing technical leadership, setting the vision, and guiding the team through the full development lifecycle-from ideation to model deployment and scaling.

View full posting on CareerOneStop → ID: 76db7294b016

Senior Data Science Engineer, GenAI Platforms and Data Infra

ADOBE INC. · Lehi, UT

Senior

2026-04-28

UT 2026-04-28

View full posting on CareerOneStop → ID: d0989f1893e7

Early Career Artificial Intelligence (AI) Data Science

Sandia National Laboratories · Albuquerque, NM

Entry-level

2026-04-28

NM 2026-04-28

View full posting on CareerOneStop → ID: 04ead090e9d5

(USA) Senior Manager, Data Science (AI Technical Lead) - Next-Gen Customer Engagement & Returns

Walmart · Bentonville, AR

Manager

2026-04-28

AR 2026-04-28

View full posting on CareerOneStop → ID: 45165b2af88f

Senior Data Scientist

Cribl, Inc · Frankfort, KY

Senior

2026-04-28

KY 2026-04-28

View full posting on CareerOneStop → ID: 40e523e3f6b8

Senior Director, AI/ML Engineering - Remote

UnitedHealth Group · Seattle, WA

Director Doctorate

2026-04-27

WA 2026-04-27

Requirements

Master's degree in Machine Learning, Artificial Intelligence, Computer Science, or a related field
15+ years of experience in AI/ML with demonstrable career progression from individual contributor to technical leadership roles
Hands-on experience with machine learning libraries and frameworks
Current and extensive hands-on experience with modern AI tools, frameworks, and methodologies
Experience with data analysis tools and techniques
Experience implementing machine learning fairness and bias mitigation techniques
Public cloud experience (Azure, and/or GCP, and/or AWS)
Comprehensive knowledge of statistical methods, machine learning algorithms, and AI principles
Proven track record of hands-on development and implementation of enterprise-scale AI SaaS solutions with measurable business impact
Demonstrated ability to balance strategic leadership with hands-on technical contribution
Demonstrated solid and current programming skills in Python or other relevant programming languages
Proven ability to build and scale AI infrastructure and operations

Preferred

PhD or Master's degree in Machine Learning, Artificial Intelligence, Computer Science, or a related field
Active practitioner with current, deep technical expertise in AI technologies and applications; Natural Language Processing (NLP) and/or Large Language Models (LLM)
Healthcare experience and FinTech solutions
Proven exceptional leadership, communication, and executive presence skills
All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $159,300 to $273,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.
*Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
_At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission._

Responsibilities

Develop and execute org-wide AI strategy and roadmap aligned with business objectives and growth initiatives
Maintain hands-on involvement in key AI projects, actively contributing to code, model development, and technical solutions
Drive innovation through research and adoption of cutting-edge AI technologies and methodologies
Establish AI governance frameworks, ethical guidelines, and best practices across the organization
Personally design, develop, and implement AI and machine learning models using statistical analysis and deep learning algorithms
Collaborate with cross-functional leadership to translate business needs into AI strategy
Collaborate with team leads in the deployment and maintenance of AI models in production environments, ensuring scalability, reliability, and cost-effectiveness
Spearhead integration of AI solutions with existing systems and applications
Establish KPIs and performance metrics for AI solutions and drive continuous improvement
Present AI vision, roadmaps, and results to executive leadership and board members
Lead research initiatives and partnerships to maintain competitive advantage in AI capabilities
Mentor, develop, and retain top AI talent while building a culture of innovation
You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

View full posting on CareerOneStop → ID: 8be85cfaac66

Principal Data Scientist

EPICOR SOFTWARE CORPORAITON · Lehi, UT

Senior

2026-04-27

UT 2026-04-27

View full posting on CareerOneStop → ID: 7c1853b01b9d

Senior Machine Learning Engineer| Uber Direct

Uber · Seattle, WA

Senior Doctorate

2026-04-26

WA 2026-04-26

Requirements

Bachelor's degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related technical field, or equivalent practical experience.
5+ years of experience building and shipping production-grade machine learning systems.
Strong proficiency in Python , plus experience with at least one additional programming language (e.g., Go, Java, C++, Scala).
Hands-on experience with modern ML frameworks such as PyTorch, TensorFlow, JAX, or Scikit-Learn .
Demonstrated experience deploying, monitoring, and maintaining ML models in production environments.
Solid understanding of statistics, feature engineering, model evaluation methodologies, and experimental design.
Strong software engineering fundamentals, including data structures, algorithms, and system design.

Preferred

Master's or PhD in Machine Learning, Computer Science, Statistics, or related field.
Experience building large-scale ML systems in a high-throughput, low-latency production environment.
Background in logistics, marketplace systems, forecasting, optimization, recommendation systems, or time-series modeling.
Experience with distributed data processing frameworks (e.g., Spark, Hive) and streaming systems (e.g., Kafka).
Familiarity with MLOps tooling such as Airflow, Kubeflow, MLflow, feature stores, and CI/CD pipelines for ML workflows.
Experience with A/B testing, experimentation frameworks, and causal inference.
Proven ability to optimize ML systems for scalability, reliability, observability, and latency.
Experience mentoring engineers and contributing to technical strategy.
*Success Attributes
*Machine Learning Depth: Strong foundation in ML theory and applied modeling, with the ability to balance trade-offs between accuracy, interpretability, and system performance.
*Engineering Excellence: Ability to design and implement scalable, maintainable ML systems that operate reliably in production.
*Ownership Mindset: End-to-end accountability for model quality, system health, and business impact.
*Cross-Functional Leadership: Ability to influence and collaborate effectively with Product, Science, and Engineering stakeholders.
*Impact Orientation: Focus on delivering measurable improvements to core business metrics through data-driven solutions.
*Why Uber Direct?
At Uber Direct, you'll help shape the future of logistics through data-driven intelligence at global scale. Your work will directly power the technology behind enterprise delivery and impact millions of customers worldwide. Join a team where experimentation, innovation, and ownership are core to our engineering culture.
For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Responsibilities

Uber Direct powers fast, reliable delivery for enterprise retailers and local businesses by leveraging Uber's world-class logistics network. As a Senior Machine Learning Engineer on the Uber Direct team, you will define and build intelligent systems that improve operational efficiency, customer experience, and predictive capabilities in real-time logistics at global scale.
You'll partner closely with Product, Data Science, and Engineering teams to design, deploy, and continually enhance machine learning-driven solutions that power core decision-making across the delivery lifecycle. Your work will directly influence key marketplace and logistics metrics across millions of global deliveries.
Develop High-Impact ML Solutions: Design, build, and productionize machine learning models that solve critical logistics problems such as ETA prediction, demand forecasting, dispatch optimization, anomaly detection, and delivery quality improvements.
Own the End-to-End ML Lifecycle: Lead projects from problem definition and data exploration through feature engineering, model development, evaluation, deployment, monitoring, and iteration.
Build Scalable ML Systems: Develop robust data pipelines, feature stores, training workflows, and model serving infrastructure that support both real-time and batch inference at scale.
Drive Business Impact: Define success metrics, run experiments, and rigorously evaluate model performance to ensure measurable improvements to KPIs such as Completion Rate, On-Time Rate, and Defect Rate.
Collaborate Cross-Functionally: Work closely with Product Managers, Data Scientists, Operations, and Backend Engineers to translate business problems into scalable ML solutions.
Technical Leadership & Mentorship: Provide technical direction, establish best practices in ML and MLOps, and mentor engineers across the team.

View full posting on CareerOneStop → ID: 2bebef2a2733

Data Scientist II - AI Assurance Researcher

Pacific Northwest National Laboratory · Seattle, WA

Mid-level Doctorate

2026-04-25

WA 2026-04-25

Requirements

BS/BA and 2 years of relevant experience -OR-
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Degree in computer science, engineering, mathematics, or a related field.
Familiarity with the current ML research landscape, particularly in explainable AI, adversarial machine learning, AI safety, and the science of deep learning.
Hands-on experience analyzing the internal structures of deep learning models, particularly large language models and large vision models.
Proficiency in PyTorch and associated deep learning libraries.
Experience designing and executing experiments on HPC systems.
Experience in translating research prototypes into deployable tools and capabilities.
Demonstrated strong communication and collaboration skills, with the ability to work effectively in a multi-disciplinary team environment.

Responsibilities

PNNL is seeking a Data Scientist II - AI Assurance Researcher who has experience in understanding, exploring, and manipulating the internal mechanics and behaviors of AI models and can provide valuable insights into the decision boundaries and mathematical fingerprints of data properties. The selected candidate should have extensive experience training models, accessing and working with data embeddings, the ability to derive theoretical queries from empirical results, and demonstrate the capacity to translate research papers and findings into mission relevant insights and tools.
Designs and executes rigorous ML experiments following community best practices, including large-scale training and evaluation on HPC infrastructure.
Evaluates AI systems across multiple dimensions, including standard performance metrics, generalization, robustness, and out-of-distribution behavior.
Analyzes the internal structures and representations of deep learning models, with emphasis on large language models and large vision models.
Assesses empirical results to identify trends, inform research direction, and recommend next steps.
Writes high-quality, well-documented research code that supports reproducibility and collaboration.
Contributes to publications and technical reports that communicate findings to both internal and external audiences.
Collaborates with senior researchers, engineers, and cross-functional teams to integrate research into broader systems and workflows.
Conducts work in secure environments with adherence to operational security requirements.
*This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

View full posting on CareerOneStop → ID: 8fb806ff29bc

Data Scientist, Labs, SCOT Forecasting and Labs

Amazon · Bellevue, WA

Mid-level Doctorate

2026-04-25

WA 2026-04-25

Requirements

3+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of data scientist experience
Bachelor's degree

Preferred

Master's degree, or PhD
Natural curiosity and desire to learn

Responsibilities

Partner with customer teams to design rigorous large-scale experiments (such as randomized controlled trials and quasi-experiments) to evaluate policy updates and model improvements across millions of products, hundreds of fulfillment nodes, and diverse business contexts
Lead the end-to-end experimentation lifecycle, from hypothesis formulation through analysis and stakeholder alignment, to inform production rollout decisions
Advance causal inference methodology for supply chain settings, including treatment effect estimation, interference modeling, and emulation techniques that accelerate policy evaluation
Build and maintain production-grade experimentation infrastructure and analytical tools using Python, SQL, Scala, and related technologies
Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform experimental design and policy development
Develop and scale supply chain emulation systems that model inventory dynamics end to end, enabling rapid offline evaluation of policy changes across millions of products without the cost and latency of live experiments
Translate complex research findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
Contribute to Amazon's scientific community and the broader research field through collaboration and publication in top-tier venues
You might start the morning reviewing results from a randomized controlled trial running across millions of products, digging into causal estimates and designing the next iteration. Later, you could be designing an experiment with a partner team where interference is unavoidable: treated and control units share fulfillment networks and inventory pools, and you need a credible strategy despite the spillover effects.
You'll build supply chain emulation systems that replicate inventory dynamics end to end, write code in Python, Scala, and SQL at a scale most scientists never encounter, and collaborate with scientists, engineers, and business teams across SCOT. Your research has a real chance of being published at top venues.
The work is hard, the problems are unsolved, and the impact is immediate. If you want to do research that ships, this is where you do it.

View full posting on CareerOneStop → ID: c5de427b9901

Data Scientist, Labs, SCOT Forecasting and Labs

Amazon · Bellevue, WA

Mid-level Doctorate

2026-04-25

WA 2026-04-25

Requirements

3+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of data scientist experience
Bachelor's degree

Preferred

Master's degree, or PhD
Natural curiosity and desire to learn

Responsibilities

Partner with customer teams to design rigorous large-scale experiments (such as randomized controlled trials and quasi-experiments) to evaluate policy updates and model improvements across millions of products, hundreds of fulfillment nodes, and diverse business contexts
Lead the end-to-end experimentation lifecycle, from hypothesis formulation through analysis and stakeholder alignment, to inform production rollout decisions
Advance causal inference methodology for supply chain settings, including treatment effect estimation, interference modeling, and emulation techniques that accelerate policy evaluation
Build and maintain production-grade experimentation infrastructure and analytical tools using Python, SQL, Scala, and related technologies
Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform experimental design and policy development
Develop and scale supply chain emulation systems that model inventory dynamics end to end, enabling rapid offline evaluation of policy changes across millions of products without the cost and latency of live experiments
Translate complex research findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
Contribute to Amazon's scientific community and the broader research field through collaboration and publication in top-tier venues
You might start the morning reviewing results from a randomized controlled trial running across millions of products, digging into causal estimates and designing the next iteration. Later, you could be designing an experiment with a partner team where interference is unavoidable: treated and control units share fulfillment networks and inventory pools, and you need a credible strategy despite the spillover effects.
You'll build supply chain emulation systems that replicate inventory dynamics end to end, write code in Python, Scala, and SQL at a scale most scientists never encounter, and collaborate with scientists, engineers, and business teams across SCOT. Your research has a real chance of being published at top venues.
The work is hard, the problems are unsolved, and the impact is immediate. If you want to do research that ships, this is where you do it.

View full posting on CareerOneStop → ID: 32120793dbf4

Data Scientist, SPX AI Lab, SPX Science

Amazon · Seattle, WA

Mid-level Master's

2026-04-25

WA 2026-04-25

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of working with or evaluating AI systems experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Preferred

Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

- Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience
- Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience.
- Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods).
- Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring.
- Apply NLP and statistical modeling techniques-including topic modeling, clustering, semantic similarity, and classification-to uncover insights from unstructured seller interactions, feedback, and content.
- Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations.
- Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams.
- Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement.
- Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI.

View full posting on CareerOneStop → ID: c879768837cc

Data Scientist, SPX AI Lab, SPX Science

Amazon · Seattle, WA

Mid-level Master's

2026-04-25

WA 2026-04-25

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of working with or evaluating AI systems experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Preferred

Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

- Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience
- Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience.
- Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods).
- Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring.
- Apply NLP and statistical modeling techniques-including topic modeling, clustering, semantic similarity, and classification-to uncover insights from unstructured seller interactions, feedback, and content.
- Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations.
- Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams.
- Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement.
- Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI.

View full posting on CareerOneStop → ID: 0bf2d38bf5af

Data Scientist, SPX AI Lab, SPX Science

Amazon · Seattle, WA

Mid-level Master's

2026-04-25

WA 2026-04-25

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of working with or evaluating AI systems experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Preferred

Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

- Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience
- Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience.
- Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods).
- Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring.
- Apply NLP and statistical modeling techniques-including topic modeling, clustering, semantic similarity, and classification-to uncover insights from unstructured seller interactions, feedback, and content.
- Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations.
- Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams.
- Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement.
- Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI.

View full posting on CareerOneStop → ID: 6c6c5b5d3d9b

Lead Data Scientist IV - GEOINT

Pacific Northwest National Laboratory · Seattle, WA

Senior Doctorate

2026-04-25

WA 2026-04-25

Requirements

BS/BA and 7+ years of relevant work experience -OR-
MS/MA and 5+ years of relevant work experience -OR-
PhD with 3+ years of relevant experience
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Advanced degree in data science, computer science, physics, mathematics, or a similar discipline.
Expertise in GEOINT workflows, including experience with remote sensing platforms, multi-modal data fusion, and advanced geospatial analytics.
Experience working with hyperspectral imaging data in the LWIR, including:
Developing and validating machine learning-based detection, classification, and unmixing algorithms
Full product pipeline experience (radiometric calibration, atmospheric correction, geometric correction, etc.)
Strong spectral sensing fundamentals (radiative transfer, reflectance/emissivity, absorption features, SNR/noise modeling, sensor characterization)
Applying ML techniques to hyperspectral data fusion for geospatial intelligence applications
Proficiency with hyperspectral analysis and visualization tools (e.g., ENVI/IDL)
Experience working with Synthetic Aperture Radar (SAR) data (complex/IQ and formed products), including:
Developing and validating both traditional signal-processing and machine learning-based detection and classification algorithms
End-to-end SAR image product conversion pipeline experience
Proficiency with SAR rendering tools
Strong knowledge of SAR/RADAR theory fundamentals (wave propagation, scattering, speckle, Doppler/geometry, calibration, etc.)
Strong proficiency in geospatial analysis tools (e.g., ArcGIS, QGIS, GDAL, GeoPandas) and development frameworks such as Python, R, TensorFlow, or PyTorch.
Experience deploying operational solutions, ensuring scalability and applicability in secure or mission-critical environments.
Proven success in proposal development and securing external funding to support technical work or research programs.
Experience working with or supporting national security mission sponsors such as the Department of Energy (DOE), Department of Defense (DoD), Department of Homeland Security (DHS), or similar organizations.
Strong communication and leadership skills, including the ability to present technical findings to diverse audiences and stakeholders and to collaborate effectively within multi-disciplinary teams.

Responsibilities

PNNL is seeking a Lead Data Scientist with expertise in data science and a passion for solving mission-critical challenges in the geospatial intelligence (GEOINT) domain. The selected candidate will contribute to research and development programs within the AI and Data Analytics Division which specializes in data science, applied mathematics, advanced analytic architectures, software engineering, and human-centered computing.
The position will work as part of interdisciplinary teams to deliver data-driven solutions that address critical national security challenges. This individual will collaborate with peers to develop machine learning (ML) models, analyze geospatial datasets, and perform research that bridges cutting-edge methods and field-ready solutions. The candidate will support PNNL's mission by contributing to impactful R&D projects that help tackle national challenges.
Successful candidates will have the opportunity to grow professionally while working on diverse, mission-focused projects. At PNNL, we foster a collaborative and innovative work environment aimed at lifelong learning, creative problem-solving, and advancing interdisciplinary, data-driven innovation.
Designs and implements innovative GEOINT data science solutions, addressing complex technical challenges related to imagery analysis, object detection, data fusion, and geospatial workflows.
Serves as a principal investigator (PI) or co-PI on projects or tasks contributing to the integration of multiple capabilities or interdisciplinary approaches.
Leads efforts to develop and deploy ML pipelines to process and analyze large quantities of geospatial data in operational environments.
Mentors and guides junior staff, fostering technical excellence and professional development within the team.
Explores and generates new ideas for proposals and business opportunities by identifying emerging national security needs related to GEOINT analytics.
Builds and maintains external partnerships to increase the technical reputation of the team and align project outcomes with sponsor priorities.
Collaborates with multi-disciplinary teams, including software engineers, geospatial analysts, and operational mission specialists, to transition research outputs into usable, field-ready solutions.
Ensures compliance with quality, safety, and security standards in all project tasks and serve as a role model for adhering to these standards.
*This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

View full posting on CareerOneStop → ID: 2609284f151f

Principal Data Scientist, Pricing Strategy

OKTA · Bellevue, WA

Senior

2026-04-25

WA 2026-04-25

Requirements

8+ years of experience in data science, analytics, pricing, strategy consulting, or a related quantitative field (B2B SaaS preferred)
Proven ability to apply statistical rigor and structured analytics to ambiguous business problems and deliver measurable impact
Experience designing measurement approaches for business initiatives (e.g., pilots, rollouts, test-and-learn), and communicating results with clarity
Strong proficiency in SQL and Python, with experience working in modern data environments (e.g., Snowflake) and BI tools (e.g., Tableau)
Ability to synthesize complex data using quantitative approaches, translate findings into clear visualizations, and deliver executive-ready insights and recommendations
Demonstrated ability to influence cross-functional senior stakeholders and lead through ambiguity

Responsibilities

Strategic Pricing Influence: Partner with Product, GTM, and Finance leadership to inform portfolio-level pricing, packaging, and discount strategy with data-driven recommendations
Advanced Analytics and Modeling: Build and operationalize models and analytical frameworks to forecast pricing impact, customer behavior, and revenue outcomes across segments and geographies
Experimentation and Pilots: Design and evaluate pilots and test-and-learn programs for new pricing initiatives, defining success criteria and measurement plans
Deep-Dive Insight Generation: Analyze large, complex datasets to uncover drivers of purchasing, discounting, retention, and monetization performance
Metrics and Dashboard Development: Establish the right KPIs and build dashboards to monitor monetization strategy effectiveness and the ROI of pricing initiatives in real time
Data Foundation Partnership: Work with Okta Data teams to shape and enhance the foundational data required for pricing analytics initiatives
Cross-Functional Execution Partnership: Translate strategy and insights into operational requirements, working with stakeholders across Sales, Legal, and Systems teams to enable implementation and adoption

View full posting on CareerOneStop → ID: be3341a262c1

Senior Data Scientist - 3031819

Apex Systems, Inc. · Redmond, WA

Senior Bachelor's

2026-04-25

WA 2026-04-25

Requirements

Bachelor's degree in a technical field such as computer science, computer engineering or related field required
8-10 years applicable experience required
Experience with database technologies
Knowledge of the ETL process
Knowledge of at least one scripting language
Strong written and oral communication skills
Strong troubleshooting and problem solving skills
Demonstrated history of success
Desire to be working with data and helping businesses make better data driven decisions

Responsibilities

This is a Marketing Data Science role. Marketing analytics experience required.
Measure what actually drives Minecraft player acquisition, reactivation, and long-term value across marketing channels. This role will own campaign post-mortems, attribution modeling, and marketing funnel analysis --- connecting upstream spend and impressions to downstream engagement and monetization outcomes. You will partner with Growth Marketing and Finance to inform budget decisions and build the measurement frameworks that scale Minecraft's marketing effectiveness. The ideal candidate blends analytical rigor with marketing intuition and can translate complex attribution results into clear recommendations for non-technical stakeholders.
Work with senior management, technical and client teams in order to determine data requirements, business data implementation approaches, best practices for advanced data manipulation, storage and analysis strategies
Write and code logical and physical database descriptions and specify identifiers of database to management system or direct others in coding descriptions
Design, implement, automate and maintain large scale enterprise data ETL processes
Modify existing databases and database management systems and/or direct programmers and analysts to make changes
Test programs or databases, correct errors and make necessary modifications

View full posting on CareerOneStop → ID: 7fa0fd0c44ec

Senior Data Scientist - 3031820

Apex Systems, Inc. · Redmond, WA

Senior Bachelor's

2026-04-25

WA 2026-04-25

Requirements

Bachelor's degree in a technical field such as computer science, computer engineering or related field required
8-10 years applicable experience required
Experience with database technologies
Knowledge of the ETL process
Knowledge of at least one scripting language
Strong written and oral communication skills
Strong troubleshooting and problem solving skills
Demonstrated history of success
Desire to be working with data and helping businesses make better data driven decisions

Responsibilities

Apex is looking for a Data Scientist for a hybrid position 3 days a week in Redmond, WA. This is a chance to work directly with Minecraft Marketplace and Minecraft Realms teams on improving content plans, monetization strategies, recommendation, and discovery. This role is analytics heavy.
Key projects: This role will contribute to digital monetization, downloadable content, and expanding user generated content offerings. They will support expanding the Marketplace to better compete in the user-generated content space, making this an especially interesting role for candidates familiar with platform s like Roblox or Fortnite.
*Ideal Background for Candidate
Strong in business analytics and data science focused on post sale monetization of digital experiences.
The ideal resume would contain experience in digital subscription based or streaming services (e.g., Netflix, Spotify)
This is a Minecraft Monetization data scientist role.
Apply advanced analytics, experimentation, and predictive modeling to optimize monetization across Minecraft's three revenue pillars: Realms subscriptions, Marketplace content sales, and Creator on Demand. This role will build LTV models, analyze cross-product spend behavior, design and read out A/B tests on pricing and UX changes, and surface insights that drive revenue growth while protecting player experience. The ideal candidate has strong statistical foundations, fluency in Python and SQL on Databricks, and experience modeling user spending behavior in games or subscription products.
Work with senior management, technical and client teams in order to determine data requirements, business data implementation approaches, best practices for advanced data manipulation, storage and analysis strategies
Write and code logical and physical database descriptions and specify identifiers of database to management system or direct others in coding descriptions
Design, implement, automate and maintain large scale enterprise data ETL processes
Modify existing databases and database management systems and/or direct programmers and analysts to make changes
Test programs or databases, correct errors and make necessary modifications

View full posting on CareerOneStop → ID: 0c5b3752de46

Senior Data Scientist III - GEOINT

Pacific Northwest National Laboratory · Seattle, WA

Senior Doctorate

2026-04-25

WA 2026-04-25

Requirements

BS/BA and 5+ years of relevant work experience -OR-
MS/MA and 3+ years of relevant work experience -OR-
PhD with 1+ year of relevant experience
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Degree in data science, computer science, physics, mathematics, or similar discipline.
Expertise in GEOINT workflows, including experience with remote sensing platforms, multi-modal data fusion, and advanced geospatial analytics.
Experience working with hyperspectral imaging data in the LWIR, including:
Developing and validating machine learning-based detection, classification, and unmixing algorithms
Full product pipeline experience (radiometric calibration, atmospheric correction, geometric correction, etc.)
Strong spectral sensing fundamentals (radiative transfer, reflectance/emissivity, absorption features, SNR/noise modeling, sensor characterization)
Proficiency with hyperspectral analysis and visualization tools (e.g., ENVI/IDL)
Experience working with Synthetic Aperture Radar (SAR) data (complex/IQ and formed products), including:
Developing and validating both traditional signal-processing and machine learning-based detection and classification algorithms
End-to-end SAR image product conversion pipeline experience
Proficiency with SAR rendering tools
Strong knowledge of SAR/RADAR theory fundamentals (wave propagation, scattering, speckle, Doppler/geometry, calibration, etc.)
Hands-on experience with geospatial analysis tools (e.g., GDAL, GeoPandas, Google Earth Engine) and machine learning frameworks (e.g., TensorFlow, PyTorch).
Proven proficiency in creating proposals and technical reports.
Strong communication and collaboration skills, with the ability to present technical findings to diverse audiences and work effectively within multi-disciplinary teams.

Responsibilities

PNNL is seeking a Senior Data Scientist with expertise in data science and a passion for solving mission-critical challenges in the geospatial intelligence (GEOINT) domain. The selected candidate will contribute to research and development programs within the AI and Data Analytics Division which specializes in data science, applied mathematics, advanced analytic architectures, software engineering, and human-centered computing.
The Data Scientist will work as part of interdisciplinary teams to deliver data-driven solutions that address critical national security challenges. This individual will collaborate with peers to develop machine learning (ML) models, analyze geospatial datasets, and perform research that bridges cutting-edge methods and field-ready solutions. The candidate will support PNNL's mission by contributing to impactful R&D projects that help tackle national challenges.
Successful candidates will have the opportunity to grow professionally while working on diverse, mission-focused projects. At PNNL, we foster a collaborative and innovative work environment aimed at lifelong learning, creative problem-solving, and advancing interdisciplinary, data-driven innovation.
Drives the execution of research by developing, testing, and deploying ML models and geospatial analytics workflows.
Takes ownership of defined tasks or small projects, proactively identifying technical challenges and proposing solutions to senior staff or project leads.
Engages with stakeholders to understand project requirements and translate them into actionable technical approaches aligned with sponsor goals.
Serves as a mentor to junior staff or interns within the team, fostering a collaborative and inclusive research environment.
Supports proposal development and business development my contributing to proposals and/or briefing sponsors.
Builds effective working relationships within your immediate team, as well as across interdisciplinary teams at the group or division level.
*This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

View full posting on CareerOneStop → ID: 7364ea01e40b

Senior Data Scientist III- AI Assurance Researcher

Pacific Northwest National Laboratory · Seattle, WA

Senior Doctorate

2026-04-25

WA 2026-04-25

Requirements

BS/BA and 5+ years of relevant work experience -OR-
MS/MA and 3+ years of relevant work experience -OR-
PhD with 1+ year of relevant experience
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Advanced degree in computer science, engineering, mathematics, or a related field.
Deep familiarity with the current ML research landscape, particularly in explainable AI, adversarial machine learning, AI safety, and the science of deep learning.
Track record of peer-reviewed publications or technical contributions in relevant research areas.
Hands-on experience analyzing the internal structures and representations of deep learning models, particularly large language models and large vision models.
Strong proficiency in PyTorch and associated deep learning libraries.
Experience designing and executing large-scale experiments on HPC systems.
Demonstrated ability to translate research prototypes into deployable tools and capabilities.
Excellent communication skills, with the ability to convey complex research findings to both technical and non-technical audiences.

Responsibilities

PNNL is seeking a Senior Data Scientist - AI Assurance Researcher who has experience in understanding, exploring, and manipulating the internal mechanics and behaviors of AI models can provides valuable insights into the decision boundaries and mathematical fingerprints of data properties. The selected candidate should have extensive experience training models, accessing and working with data embeddings, the ability to derive theoretical queries from empirical results, and demonstrate the capacity to translate research papers and findings into mission relevant insights and tools.
Defines and leads research agendas in areas such as explainable AI, adversarial machine learning, AI safety, and the science of deep learning.
Designs and executes rigorous ML experiments at scale, including large-scale training and evaluation on HPC infrastructure.
Develops novel evaluation methodologies that go beyond standard performance metrics to assess generalization, robustness, and out-of-distribution behavior.
Analyzes the internal structures and representations of deep learning models, with emphasis on large language models and large vision models.
Interprets empirical results to identify promising research directions and guide strategic investment of team resources.
Establishes best practices for research code quality, reproducibility, and integration into operational pipelines.
Mentors junior researchers and engineers, fostering a culture of scientific rigor and collaborative inquiry.
Conducts work in secure environments with adherence to operational security requirements.
*This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

View full posting on CareerOneStop → ID: 8cb2b02dbf91

Senior Machine Learning Engineer

Pacific Northwest National Laboratory · Seattle, WA

Senior Doctorate

2026-04-25

WA 2026-04-25

Requirements

BS/BA and 5+ years of relevant work experience -OR-
MS/MA and 3+ years of relevant work experience -OR-
PhD with 1+ year of relevant experience
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Degree in computer science, engineering, mathematics, or a related field.
Experience in research engineering, ML engineering, AI systems integration, or applied data science.
Strong proficiency in Python and hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face).
Demonstrated ability to navigate research codebases (e.g., Jupyter notebooks, unstructured scripts) and translate them into production-ready components.
Experience designing and deploying scalable ML pipelines or AI-enabled tools in operational or mission-critical settings.
Excellent communication and cross-functional collaboration skills, with the ability to bridge research and engineering teams.

Responsibilities

PNNL is seeking a Senior Machine Learning Engineer who has deep experience refactoring and modularizing research code for maintainability, extensibility, and reusability. The selected candidate must be able to collaborate effectively across research and engineering teams to align research goals with deployment requirements, and to develop packages, APIs, and interfaces that enable straightforward integration into mission-relevant environments. They should be fluent in Python and modern ML frameworks, and comfortable working with unstructured, experimental code.
Leads the refactoring, modularization, and optimization of research code to improve maintainability, scalability, and production readiness.
Collaborates closely with researchers to understand algorithmic intent and with engineers to ensure seamless integration into broader systems and workflows.
Architects and develops tools, pipelines, and APIs that enable deployment into mission-relevant environments.
Influences technical roadmaps and architectural decisions for AI/ML infrastructure.
Evaluates and recommend emerging tools, frameworks, and practices to keep the team at the leading edge.
Establishes and promotes best practices for translating research outputs into robust, production-quality software.
Mentors junior staff on software engineering standards, code quality, and research-to-production workflows.
Writes clear, well-documented code and leads code reviews to uphold team standards.
Conducts work in secure environments with adherence to operational security requirements.
*This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

View full posting on CareerOneStop → ID: ca763388ce4c

Software Dev Engineer, EC2 Nitro, EC2 Nitro Machine Learning Systems

Amazon · Seattle, WA

Mid-level Bachelor's

2026-04-25

WA 2026-04-25

Requirements

3+ years of non-internship professional software development experience
2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
Experience programming with at least one software programming language
1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded software applications, tools, systems, and services using: C, C++, Rust in Linux environment
1+ years of embedded software development experience

Preferred

3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Bachelor's degree in computer science or equivalent

View full posting on CareerOneStop → ID: 2e08760626ec

Staff Machine Learning Engineer, Offline Infrastructure

Unity Technologies · Bellevue, WA

Senior

2026-04-25

WA 2026-04-25

Requirements

Strong experience building large-scale ML pipelines
Experience working with distributed computing frameworks such as Ray, Spark, Flink and familiarity in the Ray ecosystem (Ray Data, Ray Train) for distributed data processing and model training
Experience building infrastructure for training data generation, dataset preparation, or ML feature pipelines
Deep experience designing and operating production-grade data pipelines
Strong programming skills in Python and experience working with large-scale distributed workloads
Experience with modern data infrastructure (data lakes, warehouses, orchestration systems, streaming platforms)
Strong systems thinking, with the ability to reason about performance, scalability, reliability, and cost tradeoffs in distributed systems
Proven ability to lead technical direction and influence architectural decisions across teams without formal authority
*Additional information
Relocation support is not available for this position

Responsibilities

*The opportunity
Unity Vector builds an offline ML platform that powers insight, experimentation, attribution, and AI-driven decision-making across the company.
Our systems operate at scale across batch and streaming data, supporting analytics, product intelligence, machine learning pipelines, and business operations. As data volume and complexity grow, our platform also supports large-scale model training, feature generation, and experimentation workflows that power production ML systems.
To support this growth, we need strong technical ownership to ensure our ML pipelines remain reliable, scalable, and architecturally sound.
We are seeking a staff ML engineer to design and evolve the large-scale offline platform. This role focuses on building reliable infrastructure for generating training datasets, orchestrating ML workflows, and enabling efficient, distributed model training at scale. You will work closely with ML engineers and platform teams to ensure our pipelines can efficiently handle growing data volumes and increasingly complex training workloads.
You will play a key role in shaping how model datasets are prepared as well as model training, validated, and delivered to distributed training systems, while ensuring the reliability, scalability, and performance of our offline ML platform.
Design and operate large-scale data pipelines that generate training datasets used for machine learning training and experimentation
Develop infrastructure that supports distributed training workflows using technologies such as Pytorch, Ray Data, and Ray Train, etc.
Integrate ML pipelines with workflow orchestration systems (e.g., Flyte, Airflow, or similar) to enable reliable multi-stage training workflows
Improve reproducibility and observability of ML pipelines through dataset validation, monitoring, and automated testing
Optimize performance and resource utilization across distributed compute systems used for data processing and model training
Partner closely with ML engineers to enable efficient large-scale experimentation and model iteration
Lead architectural improvements to ensure our offline ML pipelines remain scalable, reliable, and cost-efficient

View full posting on CareerOneStop → ID: 272915ba91ab

Data Scientist II - AI Assurance Researcher

Pacific Northwest National Laboratory · Richland, WA

Mid-level Doctorate

2026-04-25

WA 2026-04-25

Requirements

BS/BA and 2 years of relevant experience -OR-
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Degree in computer science, engineering, mathematics, or a related field.
Familiarity with the current ML research landscape, particularly in explainable AI, adversarial machine learning, AI safety, and the science of deep learning.
Hands-on experience analyzing the internal structures of deep learning models, particularly large language models and large vision models.
Proficiency in PyTorch and associated deep learning libraries.
Experience designing and executing experiments on HPC systems.
Experience in translating research prototypes into deployable tools and capabilities.
Demonstrated strong communication and collaboration skills, with the ability to work effectively in a multi-disciplinary team environment.

Responsibilities

PNNL is seeking a Data Scientist II - AI Assurance Researcher who has experience in understanding, exploring, and manipulating the internal mechanics and behaviors of AI models and can provide valuable insights into the decision boundaries and mathematical fingerprints of data properties. The selected candidate should have extensive experience training models, accessing and working with data embeddings, the ability to derive theoretical queries from empirical results, and demonstrate the capacity to translate research papers and findings into mission relevant insights and tools.
Designs and executes rigorous ML experiments following community best practices, including large-scale training and evaluation on HPC infrastructure.
Evaluates AI systems across multiple dimensions, including standard performance metrics, generalization, robustness, and out-of-distribution behavior.
Analyzes the internal structures and representations of deep learning models, with emphasis on large language models and large vision models.
Assesses empirical results to identify trends, inform research direction, and recommend next steps.
Writes high-quality, well-documented research code that supports reproducibility and collaboration.
Contributes to publications and technical reports that communicate findings to both internal and external audiences.
Collaborates with senior researchers, engineers, and cross-functional teams to integrate research into broader systems and workflows.
Conducts work in secure environments with adherence to operational security requirements.
*This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

View full posting on CareerOneStop → ID: 0c61ba8edab7

Lead Data Scientist IV - GEOINT

Pacific Northwest National Laboratory · Richland, WA

Senior Doctorate

2026-04-25

WA 2026-04-25

Requirements

BS/BA and 7+ years of relevant work experience -OR-
MS/MA and 5+ years of relevant work experience -OR-
PhD with 3+ years of relevant experience
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Advanced degree in data science, computer science, physics, mathematics, or a similar discipline.
Expertise in GEOINT workflows, including experience with remote sensing platforms, multi-modal data fusion, and advanced geospatial analytics.
Experience working with hyperspectral imaging data in the LWIR, including:
Developing and validating machine learning-based detection, classification, and unmixing algorithms
Full product pipeline experience (radiometric calibration, atmospheric correction, geometric correction, etc.)
Strong spectral sensing fundamentals (radiative transfer, reflectance/emissivity, absorption features, SNR/noise modeling, sensor characterization)
Applying ML techniques to hyperspectral data fusion for geospatial intelligence applications
Proficiency with hyperspectral analysis and visualization tools (e.g., ENVI/IDL)
Experience working with Synthetic Aperture Radar (SAR) data (complex/IQ and formed products), including:
Developing and validating both traditional signal-processing and machine learning-based detection and classification algorithms
End-to-end SAR image product conversion pipeline experience
Proficiency with SAR rendering tools
Strong knowledge of SAR/RADAR theory fundamentals (wave propagation, scattering, speckle, Doppler/geometry, calibration, etc.)
Strong proficiency in geospatial analysis tools (e.g., ArcGIS, QGIS, GDAL, GeoPandas) and development frameworks such as Python, R, TensorFlow, or PyTorch.
Experience deploying operational solutions, ensuring scalability and applicability in secure or mission-critical environments.
Proven success in proposal development and securing external funding to support technical work or research programs.
Experience working with or supporting national security mission sponsors such as the Department of Energy (DOE), Department of Defense (DoD), Department of Homeland Security (DHS), or similar organizations.
Strong communication and leadership skills, including the ability to present technical findings to diverse audiences and stakeholders and to collaborate effectively within multi-disciplinary teams.

Responsibilities

PNNL is seeking a Lead Data Scientist with expertise in data science and a passion for solving mission-critical challenges in the geospatial intelligence (GEOINT) domain. The selected candidate will contribute to research and development programs within the AI and Data Analytics Division which specializes in data science, applied mathematics, advanced analytic architectures, software engineering, and human-centered computing.
The position will work as part of interdisciplinary teams to deliver data-driven solutions that address critical national security challenges. This individual will collaborate with peers to develop machine learning (ML) models, analyze geospatial datasets, and perform research that bridges cutting-edge methods and field-ready solutions. The candidate will support PNNL's mission by contributing to impactful R&D projects that help tackle national challenges.
Successful candidates will have the opportunity to grow professionally while working on diverse, mission-focused projects. At PNNL, we foster a collaborative and innovative work environment aimed at lifelong learning, creative problem-solving, and advancing interdisciplinary, data-driven innovation.
Designs and implements innovative GEOINT data science solutions, addressing complex technical challenges related to imagery analysis, object detection, data fusion, and geospatial workflows.
Serves as a principal investigator (PI) or co-PI on projects or tasks contributing to the integration of multiple capabilities or interdisciplinary approaches.
Leads efforts to develop and deploy ML pipelines to process and analyze large quantities of geospatial data in operational environments.
Mentors and guides junior staff, fostering technical excellence and professional development within the team.
Explores and generates new ideas for proposals and business opportunities by identifying emerging national security needs related to GEOINT analytics.
Builds and maintains external partnerships to increase the technical reputation of the team and align project outcomes with sponsor priorities.
Collaborates with multi-disciplinary teams, including software engineers, geospatial analysts, and operational mission specialists, to transition research outputs into usable, field-ready solutions.
Ensures compliance with quality, safety, and security standards in all project tasks and serve as a role model for adhering to these standards.
*This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

View full posting on CareerOneStop → ID: 0500525cd2a7

Senior Data Scientist III - GEOINT

Pacific Northwest National Laboratory · Richland, WA

Senior Doctorate

2026-04-25

WA 2026-04-25

Requirements

BS/BA and 5+ years of relevant work experience -OR-
MS/MA and 3+ years of relevant work experience -OR-
PhD with 1+ year of relevant experience
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Degree in data science, computer science, physics, mathematics, or similar discipline.
Expertise in GEOINT workflows, including experience with remote sensing platforms, multi-modal data fusion, and advanced geospatial analytics.
Experience working with hyperspectral imaging data in the LWIR, including:
Developing and validating machine learning-based detection, classification, and unmixing algorithms
Full product pipeline experience (radiometric calibration, atmospheric correction, geometric correction, etc.)
Strong spectral sensing fundamentals (radiative transfer, reflectance/emissivity, absorption features, SNR/noise modeling, sensor characterization)
Proficiency with hyperspectral analysis and visualization tools (e.g., ENVI/IDL)
Experience working with Synthetic Aperture Radar (SAR) data (complex/IQ and formed products), including:
Developing and validating both traditional signal-processing and machine learning-based detection and classification algorithms
End-to-end SAR image product conversion pipeline experience
Proficiency with SAR rendering tools
Strong knowledge of SAR/RADAR theory fundamentals (wave propagation, scattering, speckle, Doppler/geometry, calibration, etc.)
Hands-on experience with geospatial analysis tools (e.g., GDAL, GeoPandas, Google Earth Engine) and machine learning frameworks (e.g., TensorFlow, PyTorch).
Proven proficiency in creating proposals and technical reports.
Strong communication and collaboration skills, with the ability to present technical findings to diverse audiences and work effectively within multi-disciplinary teams.

Responsibilities

PNNL is seeking a Senior Data Scientist with expertise in data science and a passion for solving mission-critical challenges in the geospatial intelligence (GEOINT) domain. The selected candidate will contribute to research and development programs within the AI and Data Analytics Division which specializes in data science, applied mathematics, advanced analytic architectures, software engineering, and human-centered computing.
The Data Scientist will work as part of interdisciplinary teams to deliver data-driven solutions that address critical national security challenges. This individual will collaborate with peers to develop machine learning (ML) models, analyze geospatial datasets, and perform research that bridges cutting-edge methods and field-ready solutions. The candidate will support PNNL's mission by contributing to impactful R&D projects that help tackle national challenges.
Successful candidates will have the opportunity to grow professionally while working on diverse, mission-focused projects. At PNNL, we foster a collaborative and innovative work environment aimed at lifelong learning, creative problem-solving, and advancing interdisciplinary, data-driven innovation.
Drives the execution of research by developing, testing, and deploying ML models and geospatial analytics workflows.
Takes ownership of defined tasks or small projects, proactively identifying technical challenges and proposing solutions to senior staff or project leads.
Engages with stakeholders to understand project requirements and translate them into actionable technical approaches aligned with sponsor goals.
Serves as a mentor to junior staff or interns within the team, fostering a collaborative and inclusive research environment.
Supports proposal development and business development my contributing to proposals and/or briefing sponsors.
Builds effective working relationships within your immediate team, as well as across interdisciplinary teams at the group or division level.
*This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

View full posting on CareerOneStop → ID: 7226600c24c0

Senior Data Scientist III- AI Assurance Researcher

Pacific Northwest National Laboratory · Richland, WA

Senior Doctorate

2026-04-25

WA 2026-04-25

Requirements

BS/BA and 5+ years of relevant work experience -OR-
MS/MA and 3+ years of relevant work experience -OR-
PhD with 1+ year of relevant experience
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Advanced degree in computer science, engineering, mathematics, or a related field.
Deep familiarity with the current ML research landscape, particularly in explainable AI, adversarial machine learning, AI safety, and the science of deep learning.
Track record of peer-reviewed publications or technical contributions in relevant research areas.
Hands-on experience analyzing the internal structures and representations of deep learning models, particularly large language models and large vision models.
Strong proficiency in PyTorch and associated deep learning libraries.
Experience designing and executing large-scale experiments on HPC systems.
Demonstrated ability to translate research prototypes into deployable tools and capabilities.
Excellent communication skills, with the ability to convey complex research findings to both technical and non-technical audiences.

Responsibilities

PNNL is seeking a Senior Data Scientist - AI Assurance Researcher who has experience in understanding, exploring, and manipulating the internal mechanics and behaviors of AI models can provides valuable insights into the decision boundaries and mathematical fingerprints of data properties. The selected candidate should have extensive experience training models, accessing and working with data embeddings, the ability to derive theoretical queries from empirical results, and demonstrate the capacity to translate research papers and findings into mission relevant insights and tools.
Defines and leads research agendas in areas such as explainable AI, adversarial machine learning, AI safety, and the science of deep learning.
Designs and executes rigorous ML experiments at scale, including large-scale training and evaluation on HPC infrastructure.
Develops novel evaluation methodologies that go beyond standard performance metrics to assess generalization, robustness, and out-of-distribution behavior.
Analyzes the internal structures and representations of deep learning models, with emphasis on large language models and large vision models.
Interprets empirical results to identify promising research directions and guide strategic investment of team resources.
Establishes best practices for research code quality, reproducibility, and integration into operational pipelines.
Mentors junior researchers and engineers, fostering a culture of scientific rigor and collaborative inquiry.
Conducts work in secure environments with adherence to operational security requirements.
*This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

View full posting on CareerOneStop → ID: 0b3db3637d25

Senior Machine Learning Engineer

Pacific Northwest National Laboratory · Richland, WA

Senior Doctorate

2026-04-25

WA 2026-04-25

Requirements

BS/BA and 5+ years of relevant work experience -OR-
MS/MA and 3+ years of relevant work experience -OR-
PhD with 1+ year of relevant experience
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
*Rockstar Rewards

Preferred

Degree in computer science, engineering, mathematics, or a related field.
Experience in research engineering, ML engineering, AI systems integration, or applied data science.
Strong proficiency in Python and hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face).
Demonstrated ability to navigate research codebases (e.g., Jupyter notebooks, unstructured scripts) and translate them into production-ready components.
Experience designing and deploying scalable ML pipelines or AI-enabled tools in operational or mission-critical settings.
Excellent communication and cross-functional collaboration skills, with the ability to bridge research and engineering teams.

Responsibilities

PNNL is seeking a Senior Machine Learning Engineer who has deep experience refactoring and modularizing research code for maintainability, extensibility, and reusability. The selected candidate must be able to collaborate effectively across research and engineering teams to align research goals with deployment requirements, and to develop packages, APIs, and interfaces that enable straightforward integration into mission-relevant environments. They should be fluent in Python and modern ML frameworks, and comfortable working with unstructured, experimental code.
Leads the refactoring, modularization, and optimization of research code to improve maintainability, scalability, and production readiness.
Collaborates closely with researchers to understand algorithmic intent and with engineers to ensure seamless integration into broader systems and workflows.
Architects and develops tools, pipelines, and APIs that enable deployment into mission-relevant environments.
Influences technical roadmaps and architectural decisions for AI/ML infrastructure.
Evaluates and recommend emerging tools, frameworks, and practices to keep the team at the leading edge.
Establishes and promotes best practices for translating research outputs into robust, production-quality software.
Mentors junior staff on software engineering standards, code quality, and research-to-production workflows.
Writes clear, well-documented code and leads code reviews to uphold team standards.
Conducts work in secure environments with adherence to operational security requirements.
*This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

View full posting on CareerOneStop → ID: 8859ace8103b

Data Scientist

PLURALSIGHT, LLC · Draper, UT

Mid-level

2026-04-25

UT 2026-04-25

View full posting on CareerOneStop → ID: 08f19a4d100c

AI/ML Engineer II

USAA · Phoenix, AZ

Mid-level

2026-04-25

AZ 2026-04-25

View full posting on CareerOneStop → ID: 76e67fa1e59d

(USA) Senior Manager, Data Science - eCommerce Strategy

Walmart · Bentonville, AR

Manager

2026-04-25

AR 2026-04-25

View full posting on CareerOneStop → ID: eac9aacbad2d

Staff Machine Learning Engineer, AI Researcher

Cribl, Inc · Frankfort, KY

Senior

2026-04-25

KY 2026-04-25

View full posting on CareerOneStop → ID: bccbca4170ca

(Fall 2026) Annapurna Labs at AWS Internship (US) - Machine Learning Systems & Silicon Innovation

Amazon · Seattle, WA

Intern Doctorate

2026-04-24

WA 2026-04-24

Requirements

Work 40 hours/week minimum and commit to 12 week internship maximum
Currently pursuing a BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related technical field
Must be enrolled in a full-time degree program at time of application and returning to school after the internship
Programming experience in C, C++, Python, or similar languages
Experience in two or more of the following areas: 1. Systems programming or low-level software development 2. Compiler design or optimization 3. Machine learning frameworks (PyTorch, JAX, TensorFlow) 4. Distributed systems or parallel computing 5. Performance analysis and optimization 6. Hardware design (RTL, Verilog, FPGA development)

Preferred

Previous internship, research, or project experience in hardware/software co-design, ML systems, or computer architecture
Contributions to open-source projects or research publications
Completed or currently enrolled in coursework covering machine learning, parallel computing, computer architecture and/or compiler construction

View full posting on CareerOneStop → ID: 4a08e5acb3e3

Business Data Scientist, Marketing Analytics

BECU · Seattle, WA

Mid-level

2026-04-24

WA 2026-04-24

Responsibilities

*Partner with Marketing to Define and Solve Problems - Work closely with marketing stakeholders to understand business challenges, define success metrics, and translate needs into analytical approaches that drive performance across campaigns and channels.
*Design and Deliver Data-Driven Solutions - Apply statistical analysis and machine learning to develop solutions that address business needs, then present findings, influence decisions, and gain alignment on adoption.
*Lead Experimentation and Optimization - Develop and manage testing frameworks (A/B testing, campaign experimentation) across channels and markets. Analyze results and provide clear recommendations to improve performance and inform future strategy.
*Translate Results into Business Impact - Clearly communicate insights and quantify outcomes (e.g., campaign performance lift, engagement improvements, ROI) to ensure stakeholders understand the value and

View full posting on CareerOneStop → ID: 5cae691f93c2

Master's Fall Machine Learning Internship (ATG - Visual Search)

Pinterest, Inc. · Seattle, WA

Intern Master's

2026-04-24

WA 2026-04-24

Requirements

This role will be on our Visual Search team. We are looking for candidates with experience in Computer Vision, Visual Search, User Understanding, Generative AI, and LLMs.
Ability to legally work full time (40 hours/week) from September-December 2026
Working towards a Master's degree in Computer Science, ML, NLP, Statistics, Informati

Responsibilities

Develop and launch new user features using unique internal datasets and ML techniques, especially in computer vision, generative AI, and responsible AI.
Gain hands-on experience with production ML systems, including algorithmic research, infrastructure, data engineering, training, inference, and product, to deliver innovative solutions. You will be exposed to full-stack production ML systems.
Leverage frontier AI tools and agents to accelerate engineering implementation, including prototyping and experimentation work.
Validate AI-generated outputs through testing, code review, and critical thinking, ensuring solutions are accurate, maintainable, secure, and aligned with team standards.
Use AI to better understand unfamiliar code, investigate bugs, and summarize technical context or documentation.
Contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
Write clean, efficient, and sustainable code
Take proactive ownership over the completion and quality of your tasks and project with minimal guidance from your mentor, manager, and peers

View full posting on CareerOneStop → ID: 52fd99247f6f

PhD Fall Machine Learning Intern (ATG - Visual, Multimodal, and Recommender Syst

Pinterest, Inc. · Seattle, WA

Intern

2026-04-24

WA 2026-04-24

Requirements

This role will be on our Visual Search or Applied Science teams. We are looking for candidates with experience in Computer Vision, Visual Search, User Understanding, Recommendation Systems, Reinforcement Learning, ML efficiency optimization, Generative AI, and LLMs.
Ability to legally work ful

Responsibilities

Develop and launch new user features using unique internal datasets and ML techniques, especially in recommendation systems, computer vision, representation learning, generative AI, and responsible AI.
Gain hands-on experience with production ML systems, including algorithmic research, infrastructure, data engineering, training, inference, and product, to deliver innovative solutions. You will be exposed to full-stack production ML systems.
Leverage frontier AI tools and agents to accelerate engineering implementation, including prototyping and experimentation work.
Validate AI-generated outputs through testing, code review, and critical thinking, ensuring solutions are accurate, maintainable, secure, and aligned with team standards.
Use AI to better understand unfamiliar code, investigate bugs, and summarize technical context or documentation.
Contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
Write clean, efficient, and sustainable code
Take proactive ownership over the completion and quality of your tasks and project with minimal guidance from your mentor, manager, and peers

View full posting on CareerOneStop → ID: 98c11f0b8de2

Principal Machine Learning Engineer, Ads Delivery

Pinterest, Inc. · Seattle, WA

Senior

2026-04-24

WA 2026-04-24

Requirements

Degree in Computer Science, Machine Learning, Statistics or related field.
10+ years of professional experience as a hands-on engineer and technical leader leading multiple projects.
Strong software engineering and mathematical skills with knowledge of statistical methods.
Hands-on experience with large-scale online e-commerce systems is a plus.
Background in computational advertising is preferred.
We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
This role will need to be in the office for in-person collaboration 1-2 times/month, and therefore needs to be in a commutable distance from one of the following offices: San Francisco, Palo Alto, Seattle.

Preferred

Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration

Responsibilities

Build and improve backend systems and statistical models that underlay the marketplace to maximize value for Pinners, Partners and Pinterest.
Define and implement experiments to understand long term Marketplace effects.
Develop strategies to balance long and short term business objectives.
Drive multi-functional collaboration with peers and partners across the company to improve knowledge of marketplace design and operations.

View full posting on CareerOneStop → ID: a768d81dc5a9

Sr. Machine Learning Engineer, Core Engineering

Pinterest, Inc. · Seattle, WA

Senior Doctorate

2026-04-24

WA 2026-04-24

Requirements

4+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
Degree in computer science, machine learning, statistics, or related field

Preferred

Publications at top ML conferences
Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
Expertise in scalable realtime systems that process stream data
Passion for applied ML and the Pinterest product
MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences, related field, or equivalent experience.

Responsibilities

Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
Work in a high-impact environment with quick experimentation and product launches
Keeping up with industry trends in recommendation systems

View full posting on CareerOneStop → ID: c0c2436e78e6

Staff Data Scientist

Visa Usa Inc · Bellevue, WA

Senior

2026-04-24

WA 2026-04-24

Responsibilities

Provides technical expertise and mentors others to implement extensible, maintainable, and reusable code, defines framework, principles, coding patterns, guidelines, styles, and standard methodologies, and adheres to all security requirements for the application of artificial intelligence and data science.
Develops strategies for and leads team's efforts to drive efficiencies across data extraction and ensure data quality and completeness using data wrangling, complex data modeling, and artificial intelligence.
Ensures adherence to data management principles, governance, process, and tools to maintain data quality across products.
Advises on technical specifications during discussions with collaborators (e.g., Product owners, business partners, Cybersecurity) to identify and clarify sophisticated technical or business requirements and identify business needs and upstream and/or downstream system/application dependencies.
Defines technical standards for the design and documents the architecture for a complex product, using existing architecture design patterns.
Oversees and establishes unit testing requirements of unit testing to confirm functional capability of code, acts as subject matter expert in testing for coding standards and security scans, strategically leads user acceptance testing in collaboration with customer across multiple domains.
Identifies complex trends across relevant data sources and uses insights to plan platform-wide future solution updates. Identifies opportunities and defines roadmap for software upgrades and server patches for security remediation where applicable.
Identifies complex trends across relevant data sources and uses insights to plan platform-wide future solution updates. Identifies opportunities and defines roadmap for software upgrades and server patches for security remediation where app

View full posting on CareerOneStop → ID: 9216b777c109

Staff Machine Learning Engineer, Conversion Visibility

Pinterest, Inc. · Seattle, WA

Senior

2026-04-24

WA 2026-04-24

Requirements

Experience building and deploying large-scale ML systems in production (e.g., ads, measurement, recommendation, ranking, or search), with strong end-to-end ownership from problem scoping through evaluation and experimentation, and solid software engineering skills in at least one modern language (e.g., Python, Java) and large-scale data systems.
Degree in computer sci

Responsibilities

Lead the design and implementation of identity and conversion signal models (e.g., user match prediction, conversion type/value prediction, probabilistic attribution and deduplication) that improve match precision/recall and downstream conversion quality across web and app surfaces.
Own one or more major identity prediction initiatives end-to-end-from problem framing, label and feature design, and offline evaluation through production deployment and online experimentation.
Build and evolve ML-powered components in the conversion visibility pipeline, partnering with infra teams to create scalable, low-latency systems for ingesting, enriching, and exposing conversion signals to ranking, bidding, measurement, and reporting stacks.
Establish ML development best practices (data quality, feature pipelines, evaluation, experimentation) within Conversion Visibility, and mentor engineers so non-ML partners can confidently contribute to ML-powered components.
Collaborate closely with Ads Ranking & Bidding, Measurement Products, and Conversion Ingestion & Attribution teams to define interfaces, SLAs, and success metrics that ensure identity and signal models plug cleanly into the broader ads ecosystem.
Use AI to accelerate analysis and iteration on model ideas and architectures, while applying strong judgment, testing, and verification to ensure correctness, reliability, and advertiser trust.
Apply LLM-powered tools to synthesize experiment results, technical docs, and partner feedback into clear options and recommendations, helping the team explore more approaches and converge on high-impact solutions faster.

View full posting on CareerOneStop → ID: 31604ea617d1

Distinguished Data Scientist: Associate AI Experience

Walmart · Bentonville, AR

Senior

2026-04-24

AR 2026-04-24

View full posting on CareerOneStop → ID: 4af25613619c

Principal Data Scientist: Associate AI experience

Walmart · Bentonville, AR

Senior

2026-04-24

AR 2026-04-24

View full posting on CareerOneStop → ID: cbe0def7d30d

Senior Data Scientist: Associate AI Experience

Walmart · Bentonville, AR

Senior

2026-04-24

AR 2026-04-24

View full posting on CareerOneStop → ID: c91c5e2912c2

Senior Data Scientist

Guidehouse · Huntsville, AL

Senior

2026-04-24

AL 2026-04-24

View full posting on CareerOneStop → ID: 2fcb98cf2f63

(USA) Senior Manager, Data Science

Walmart · Bellevue, WA

Manager Doctorate

2026-04-23

WA 2026-04-23

Requirements

Deep understanding of machine learning, statistical modeling, and data science techniques used for risk mitigation in e-commerce or marketplace environments.
Proven ability to build, deploy, and optimize complex data science models to identify and mitigate fraud, performance, and operational risks.
Proficiency in tools and languages such as Python, R, Spark, Scala , and machine learning frameworks (e.g., TensorFlow, PyTorch, XGBoost) to develop and deploy risk models.
Ability to understand the end-to-end risk management process, from data ingestion and feature engineering to model deployment and real-time decision making.
5-8 years of experience in leading teams or projects related to data science, including mentoring junior data scientists and guiding technical teams toward best practices in model development and deployment.
Comfortable navigating complex and uncertain situations, making data-driven decisions to improve risk management strategies in a fast-evolving environment.
Strong ability to translate complex data science concepts into clear, actionable insights for non-technical stakeholders across the organization.
Understanding how data science and risk management intersect with broader business objectives and the ability to align risk strategies with organizational goals.
Option 1 : Bachelor's degree in Statistics, Computer Science, Data Science, Mathematics, or related field, with 5-8 years of hands-on experience in data science, machine learning, or risk management.
Option 2 : Master's degree in a related field (e.g., Data Science, Machine Learning, Statistics, Applied Mathematics) with at least 3-5 years of applied experience working on data-driven risk management or fraud prevention.
Option 3 : 8-10 years of direct experience in data science, machine learning, or applied risk management within an e-commerce or marketplace setting.
_Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications._
Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related field.

Preferred

Expertise in using advanced machine learning techniques such as deep learning, reinforcement learning, or anomaly detection for fraud detection or risk mitigation.
Experience with big data technologies like Apache Spark , Hadoop , and cloud-based data solutions (e.g., AWS, Google Cloud) to build scalable risk management platforms.
Proficiency in data manipulation and analysis tools such as Pandas, NumPy , and SQL for data wrangling, feature engineering, and analysis.
Strong background in model evaluation techniques including ROC/AUC, confusion matrices, precision/recall, and F1 scores, as well as experience with A/B testing and model validation
_Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications._
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart's accessibility standards and guidelines for supporting an inclusive culture.
Masters: Business Administration, Masters: Information Systems, Masters: Statistics
*Primary Location...
10900 Ne 4th St, Bellevue, WA 98004, United States of America
Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.

Responsibilities

The Senior Manager, DataScience will lead a team of data scientists to define, implement, test, and deploy decision strategies aimed at mitigating fraud and performance risks for Walmart Marketplace. In this role, you will work closely with cross-functional teams, including product, engineering, and data science, to continuously monitor, investigate, and respond to emerging risk trends. You'll be responsible for leveraging advanced data science methodologies to develop and refine risk management models, ensuring the strategies are effective and scalable across both domestic and international portfolios.
*How You'll Make an Impact:
Drive Data Science Innovation to protect the integrity of the Marketplace by applying advanced statistical methods, machine learning, and AI techniques to identify and mitigate fraud and performance risks.
Support Marketplace Growth by designing and implementing scalable, data-driven risk management solutions that align with key business objectives and growth targets.
Provide technical leadership and mentorship to your team, overseeing the development of decision models, managing model performance, and ensuring they are optimized for both accuracy and scalability.
Apply Advanced Data Science Techniques such as predictive modeling, supervised and unsupervised machine learning, deep learning, and anomaly detection to continuously improve risk strategies.
Collaborate Across Teams to integrate data science models with business processes, ensuring alignment between product, engineering, and data teams to address key risk areas effectively.
Monitor the performance of deployed models, identify opportunities for improvement, and iterate to enhance their predictive power and robustness in mitigating risks.
Develop Test & Measurement Frameworks to validate model effectiveness, utilizing rigorous A/B testing, statistical testing, and model evaluation to refine decision strategies.
Foster Innovation by exploring cutting-edge data science techniques, identifying opportunities to optimize decision-making, and driving improvements in risk management capabilities.

View full posting on CareerOneStop → ID: 4bb83fb26716

Data Science Intern

Milliman, Inc · Seattle, WA

Intern

2026-04-23

WA 2026-04-23

Requirements

Current graduate student pursuing a degree in data science, mathematics, statistics, computer science, informatics or business/economics majo
Completion of several data science college courses
Understanding of healthcare data and previous healthcare data analysis experience
Fluency in SQL, R, Python
Able to employ a variety of supervised and unsupervised machine learning methods (knowledge of large-scale machine learning is a plus)
Client-service oriented
Effective oral and written communication
Makes the most of every opportunity to learn
Team player with positive and energetic attitude
Proactively seeks out possible solutions to a problem
Strong attention to detail

View full posting on CareerOneStop → ID: 750352a9d24a

Engineering Manager, Machine Learning Operations

PitchBook Data · Seattle, WA

Manager

2026-04-23

WA 2026-04-23

Responsibilities

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.
We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other's words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!
As an Engineering Manager, Machine Learning (ML) Operations in the Technology & Engineering division, you will be responsible for leading and managing PitchBook's MLOps team. The team is responsible for enabling PitchBook's Machine Learning teams and practitioners by providing tools and golden paths that optimize all aspects of the Machine Learning Development Life Cycle (MLDLC). Your team's work will support projects in a variety of domains, including Generative AI (GenAI), Large Language Models (LLMs), Natural Language Processing (NLP), Classification, and Regression. Your role will be critical in driving AI (Artificial Intelligence) innovations across the organization.
Lead the MLOps team direction and execution (operations, processes, practices, and standards), working closely with engineering leadership and product management to craft roadmaps, define KPIs, and achieve success criteria
Ensure effective communication and coordination across geographically dispersed teams. Oversee the enablement of scalable solutions that meet high standards of reliability and efficiency
Champion the adoption and integration of ML best practices at PitchBook, fostering a culture of innovation and experimentation to drive the development of high-quality AI products
Serve as a force multiplier by removing roadblocks, implementing process improvements, providing frequent and actionable feedback to team members, and building practices for ideation and innovation
Bridge the gap between business/product needs and execution, including building and delivering on group-level objectives and key results, identifying resource needs, and building execution plans for initiatives
Ensure MLOps roadmap items are delivered on time and have exceptional quality
Learn constantly and be passionate about discovering new tools, technologies, libraries, and frameworks(commercial and open source), that can be leveraged to improve PitchBook's AI capabilities
Describe technical content in intuitive ways for a variety of audiences, adapting communication from highly technical deep dives with engineers

View full posting on CareerOneStop → ID: a3005c69a3e3

Machine Learning Engineer

Indeed · Seattle, WA

Mid-level Master's

2026-04-23

WA 2026-04-23

Responsibilities

The Machine Learning Engineer I role partners closely with business partners across various functions to help execute strategic initiatives that increase revenue, drive operational scale, and improve efficiency for continuous growth. As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source packages and research publications, and creatively adapt models for solving business problems across Indeed.
Work spans classical ML through LLM systems. You improve search and retrieval quality using real user signals. Execution includes experiments, iteration, and production reliability at scale. You collaborate with engineers, data scientists, and product teams to define problems, test approaches, and ship measurable improvements.
Build AI/ML systems for search, ranking, and recommendations
Develop LLM retrieval and generation workflows
Improve search and ranking relevance
Design metrics and run experiments
Monitor model quality, latency, and cost
Debug data, models, and system issues
Build training, inference, and eval pipelines
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 2 years of related experience; or an advanced degree without experience
Experience building ML models in Python; solid software engineering and algorithms fundamentals
Experience developing backend services in Java/Kotlin for ML-driven systems and features
Experience writing clean, testable, and maintainable production code
Experience working with structured and unstructured data, including SQL for large-scale data querying, and building scalable data pipelines and features from data
Experience integrating ML models into search systems using engines such as OpenSearch or similar, with familiarity in container orchestration for deployment with senior guidance
Excellent understanding of model evaluation techniques, feature engineering, experiment design, and familiarity with LLM systems (RAG, embeddings, output evaluation)

View full posting on CareerOneStop → ID: 8e3fc20531d1

Principal Product Manager, Data Science & Market Research

Microsoft Corporation · Redmond, WA

Manager Bachelor's

2026-04-23

WA 2026-04-23

Requirements

Bachelor's Degree AND 8+ years experience in product/service/program management or software development OR equivalent experience..
*Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:

Preferred

8 years of experience in product management, data science, market research, or strategic analytics, preferably in a platform or developer-focused organization.
Solid quantitative skills with demonstrated ability to design research, analyze large datasets, and extract actionable insights.
Ability to translate data and research findings into product strategy and executive-ready recommendations.
Strong communication skills with the ability to present complex analysis clearly to technical and non-technical audiences.
Experience working cross-functionally with engineering, product, and business teams.
Experience with developer platforms, developer tools, or application frameworks.
Familiarity with telemetry systems, experimentation frameworks, or BI/analytics platforms (e.g., Power BI, Kusto, Azure Data Explorer).
Background in competitive intelligence, market sizing, or ecosystem analysis for technology platforms.
Understanding of the Windows developer ecosystem, including Win32, .NET, WinUI, and cross-platform frameworks.
Experience with data visualization and building executive dashboards that drive organizational alignment.
Product Management IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Responsibilities

Define and own the data science and market research strategy for the Windows Platform & Developer organization, aligning research priorities to business and product goals.
Build and maintain analytical frameworks that track platform health, developer adoption, ecosystem growth, and competitive positioning across Windows, macOS, Linux, and web/cross-platform alternatives.
Deliver actionable market intelligence on developer trends, framework adoption and enterprise modernization patterns.
Partner with engineering, product, and leadership teams to define KPIs, instrument telemetry, and build dashboards that drive data-informed decision-making.
Lead primary and secondary research-developer surveys, competitive analysis, win/loss studies, and ecosystem assessments-to surface opportunities and risks.
Translate complex data into clear, compelling narratives for senior leadership to support investment decisions, roadmap prioritization, and executive reviews.
Engage with developer communities, enterprise customers, ISV partners, and internal stakeholders to validate hypotheses and ground insights in real-world signals.

View full posting on CareerOneStop → ID: ba3e52ea23e1

Senior Data Scientist, Marketing Analytics

BECU · Seattle, WA

Senior

2026-04-23

WA 2026-04-23

Responsibilities

*Partner with Marketing to Define and Solve Problems - Work closely with marketing stakeholders to understand business challenges, define success metrics, and translate needs into analytical approaches that drive performance across campaigns and channels.
*Design and Deliver Data-Driven Solutions - Apply statistical analysis and machine learning to develop solutions that address business needs, then present findings, influence decisions, and gain alignment on adoption.
*Lead Experimentation and Optimization - Develop and manage testing frameworks (A/B testing, campaign experimentation) across channels and markets. Analyze results and provide clear recommendations to improve performance and inform future strategy.
*Translate Results into Business Impact - Clearly communicate insights and quantify outcomes (e.g., campaign performance lift, engagement improvements, ROI) to ensure stakeholders understand the value and

View full posting on CareerOneStop → ID: a2cb3f78731a

Sr. Machine Learning Engineer

PitchBook Data · Seattle, WA

Senior

2026-04-23

WA 2026-04-23

Responsibilities

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.
We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other's words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!
As a Senior Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook's wealth of structured and unstructured data including reports, news, and other textual content. This role requires deep technical expertise in advanced data analytics and machine learning, as well as a hands-on approach to designing, building, and optimizing ML solutions that power user-facing features on the PitchBook Platform.
You will be deeply involved in the end-to-end development and operationalization of ML models, including their architecture, training, deployment, and ongoing maintenance. Your focus will span across natural language processing (NLP), generative AI (GenAI), large language models (LLMs), and scalable data systems. You will be expected to tackle complex technical challenges, contribute to architectural decisions, and collaborate closely with other engineers, data scientists, and product managers to ensure that your work aligns with business goals and AI/ML strategy.
Your contributions will help unlock unique value for PitchBook customers by improving the speed, discoverability, quality, and quantity of insights available on the platform. This includes developing models that can infer meaning and structure from millions of discrete data sources, and applying ML to enrich our datasets with predictive and generative intelligence. As a senior engineer, you will take ownership of key technical components and ensure that our systems meet the highest standards of performance, reliability, and security.
Deliver high-impact AI and ML capabilities that drive insight generation on the PitchBook Platform. Ensure your work contributes to broader business goals and is aligned with the team's strategic priorities
Provide hands-on expertise in designing, building, and deploying AI/ML models and services with a focus on NLP, summarization, semantic search, classification, and prediction. Contribute to the development of scalable, high-performance systems that meet production-grade reliability

View full posting on CareerOneStop → ID: fcf59307ae85

Staff Machine Learning Engineer - Cortex Code Quality

Snowflake Inc. · Bellevue, WA

Senior Doctorate

2026-04-23

WA 2026-04-23

Requirements

Bachelor's degree in Computer Science, Engineering, Statistics, or a related field. Master's or higher preferred but not a requirement.
8+ years of experience shipping AI/ML-backed software in production, including Staff-level ownership of technical direction, cross-team delivery, and mentoring.
Strong track record building and operating eval harnesses, measurement, and/or experimentation loops for LLM/agent systems-not only one-off benchmarks.
Proficiency in programming languages such as Python, TypeScript, Go (strong in at least two).
Exceptional communication skills: crisp writeups, constructive debate, and ability to influence without authority across engineering and product.
(Optional) Experience with data engineering pipelines (dbt, Airflow), data modeling, data analysis, retrieval systems, and semantic layers is a plus.

Responsibilities

The Cortex Code team is building the future of coding agents for working with data. See our flagship product in action: Cortex Code in Action: Live Demos + AMA.
As a Staff MLE/AI Engineer on Cortex Code Quality, you will help define architect agent behavior at enterprise scale by building the agentic systems and methodology that make our users build cutting edge agentic systems that are efficient,repeatable, auditable, and shippable. You'll partner with modeling, platform, and product leadership to turn customer pain into golden scenarios, metrics, and experiment loops that the whole team can trust.
What you will do in this role:
Agent strategy & systems: Own major pillars of the quality stack: tuning agent behavior to engage on next generation agentic coding tasks.
Hill-climb infrastructure: Design and evolve pipelines and tooling that support large-scale experimentation, error mining, and iteration on prompts/tools/workflows with clear before/after signals.
Deep analysis & prioritization: Lead postmortems on quality regressions; cluster failure modes; translate findings into a prioritized roadmap for engineering and modeling partners.
Cross-functional leadership: Align product, infra, and applied AI on what "good" means for critical customer workflows; mentor engineers and uplevel eval craft across the team.
Production-minded rigor: Ensure quality systems are dependable in practice-reproducible runs, stable datasets, versioning, and operational clarity when things drift.

View full posting on CareerOneStop → ID: 899cb9c7d831

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Olympia, WA

Senior Doctorate

2026-04-23

WA 2026-04-23

Requirements

Data Scientist Analyst -
Bachelor's Degree in Computer Science or Mathematics/Statistics and 2 or more years of experience in transforming data and developing insights for use in business decision area OR
High School Diploma or Equivalent in Computer Science or Mathematics/Statistics and 4 or more years of experience in transforming data and developing insights for use in business decision area OR
Zurich Certified Insurance Apprentice including an Associate Degree in Computer Science or Mathematics/Statistics and 2 or more years of experience in transforming data and developing insights for use in business decision area AND
Experience applying data transformation techniques such as exact and probabilistic matching methods; fuzzy matching, text mining, and data reduction
Sr Data Scientist Analyst -
High School Diploma or Equivalent with 7 or more years of experience in Computer Science, Statistics or Mathematics and experience transforming data in the business analysis area OR
Zurich Certified Insurance Apprentice including an Associate Degree in Computer Science, Statistics or Mathematics and 5 or more years of experience transforming data in the business analysis area OR
Bachelor's Degree in Computer Science, Statistics or Mathematics and 5 or more years of experience transforming data in the business analysis area OR
Master's Degree in Computer Science, Statistics or Mathematics and 3 or more years of experience transforming data in the business analysis area OR
PhD in Computer Science, Statistics or Mathematics and 0 or more years of experience transforming data in the business analysis area

Preferred

Possesses strong crop insurance knowledge and technical expertise
Understanding how MPCI (multi-peril crop insurance) products work and how they are priced
Experience with extracting data from relational databases
Advanced knowledge of statistical techniques and their application to business decisions
Ability to develop actionable solutions to business challenges
Advanced analytical and problem-solving skills
Strong verbal and communication skills
Your pay at Zurich is based on your role, location, skills, and experience. We follow local laws to ensure fair compensation. You may also be eligible for bonuses and merit increases. If your expectations are above the listed range, we still encourage you to apply-your unique background matters to us.
The combined salary range for this position is $87,200 - $188,700. The proposed salary range for the Data Scientist Analyst is $87,200 - $142,700, with short-term incentive bonus eligibility set at 10%.?The proposed salary range for the Sr Data Scientist Analyst is $115,200 - $188,700, with short-term incentive bonus eligibility set at 15%.
We offer competitive pay and comprehensive benefits for employees and their families. [Learn more about Total Rewards here .]
At Zurich, we value your ideas and experience. We offer growth, inclusion, and a supportive environment-so you can help shape the future of insurance. Zurich North America is a leader in risk management, with over 150 years of expertise and coverage across 25+ industries, including 90% of the Fortune 500®.
Join us for a brighter future-for yourself and our customers.

View full posting on CareerOneStop → ID: ee0fd960678e

Machine Learning Engineer

Indeed · Portland, OR

Mid-level Master's

2026-04-23

WA 2026-04-23

Responsibilities

The Machine Learning Engineer I role partners closely with business partners across various functions to help execute strategic initiatives that increase revenue, drive operational scale, and improve efficiency for continuous growth. As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source packages and research publications, and creatively adapt models for solving business problems across Indeed.
Work spans classical ML through LLM systems. You improve search and retrieval quality using real user signals. Execution includes experiments, iteration, and production reliability at scale. You collaborate with engineers, data scientists, and product teams to define problems, test approaches, and ship measurable improvements.
Build AI/ML systems for search, ranking, and recommendations
Develop LLM retrieval and generation workflows
Improve search and ranking relevance
Design metrics and run experiments
Monitor model quality, latency, and cost
Debug data, models, and system issues
Build training, inference, and eval pipelines
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 2 years of related experience; or an advanced degree without experience
Experience building ML models in Python; solid software engineering and algorithms fundamentals
Experience developing backend services in Java/Kotlin for ML-driven systems and features
Experience writing clean, testable, and maintainable production code
Experience working with structured and unstructured data, including SQL for large-scale data querying, and building scalable data pipelines and features from data
Experience integrating ML models into search systems using engines such as OpenSearch or similar, with familiarity in container orchestration for deployment with senior guidance
Excellent understanding of model evaluation techniques, feature engineering, experiment design, and familiarity with LLM systems (RAG, embeddings, output evaluation)

View full posting on CareerOneStop → ID: 798a789e964a

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Boise, ID

Senior

2026-04-23

ID 2026-04-23

View full posting on CareerOneStop → ID: 2245bf455912

Machine Learning Engineer

Indeed · Boise, ID

Mid-level

2026-04-23

ID 2026-04-23

View full posting on CareerOneStop → ID: 1ea1ccdbe7c3

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Salem, OR

Senior

2026-04-23

OR 2026-04-23

View full posting on CareerOneStop → ID: c759940118e4

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Helena, MT

Senior

2026-04-23

MT 2026-04-23

View full posting on CareerOneStop → ID: 97d24ac8900b

Machine Learning Engineer

Indeed · Helena, MT

Mid-level

2026-04-23

MT 2026-04-23

View full posting on CareerOneStop → ID: 3533ec2c9f2f

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Cheyenne, WY

Senior

2026-04-23

WY 2026-04-23

View full posting on CareerOneStop → ID: f56e2a604684

Machine Learning Engineer

Indeed · Cheyenne, WY

Mid-level

2026-04-23

WY 2026-04-23

View full posting on CareerOneStop → ID: 87b5cd3ef4f9

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Salt Lake City, UT

Senior

2026-04-23

UT 2026-04-23

View full posting on CareerOneStop → ID: d2f07740f287

Machine Learning Engineer

Indeed · Salt Lake City, UT

Mid-level

2026-04-23

UT 2026-04-23

View full posting on CareerOneStop → ID: 8f12b4b4ebdd

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Carson City, NV

Senior

2026-04-23

NV 2026-04-23

View full posting on CareerOneStop → ID: b6a76076ed52

Machine Learning Engineer

Indeed · Las Vegas, NV

Mid-level

2026-04-23

NV 2026-04-23

View full posting on CareerOneStop → ID: 3d915a3b0830

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Bismarck, ND

Senior

2026-04-23

ND 2026-04-23

View full posting on CareerOneStop → ID: b08082ceefcc

Machine Learning Engineer

Indeed · Bismarck, ND

Mid-level

2026-04-23

ND 2026-04-23

View full posting on CareerOneStop → ID: f99c11ec59f8

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Pierre, SD

Senior

2026-04-23

SD 2026-04-23

View full posting on CareerOneStop → ID: fd1383a928bc

Machine Learning Engineer

Indeed · Sioux Falls, SD

Mid-level

2026-04-23

SD 2026-04-23

View full posting on CareerOneStop → ID: e5080e1bd243

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Santa Fe, NM

Senior

2026-04-23

NM 2026-04-23

View full posting on CareerOneStop → ID: 85b586a568e4

Machine Learning Engineer

Indeed · Albuquerque, NM

Mid-level

2026-04-23

NM 2026-04-23

View full posting on CareerOneStop → ID: 911eed7fe60c

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Lincoln, NE

Senior

2026-04-23

NE 2026-04-23

View full posting on CareerOneStop → ID: 42e758392cb8

Machine Learning Engineer

Indeed · Omaha, NE

Mid-level

2026-04-23

NE 2026-04-23

View full posting on CareerOneStop → ID: 2b0ea217ace1

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Topeka, KS

Senior

2026-04-23

KS 2026-04-23

View full posting on CareerOneStop → ID: a2fa133c9b4d

Machine Learning Engineer

Indeed · Kansas City, KS

Mid-level

2026-04-23

KS 2026-04-23

View full posting on CareerOneStop → ID: 1ed93043eaa8

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Oklahoma City, OK

Senior

2026-04-23

OK 2026-04-23

View full posting on CareerOneStop → ID: 32fc0eff2d93

Machine Learning Engineer

Indeed · Oklahoma City, OK

Mid-level

2026-04-23

OK 2026-04-23

View full posting on CareerOneStop → ID: 6801b18b8bad

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Des Moines, IA

Senior

2026-04-23

IA 2026-04-23

View full posting on CareerOneStop → ID: 1c0b4d639a79

Machine Learning Engineer

Indeed · Des Moines, IA

Mid-level

2026-04-23

IA 2026-04-23

View full posting on CareerOneStop → ID: ac9a36717f79

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Jefferson City, MO

Senior

2026-04-23

MO 2026-04-23

View full posting on CareerOneStop → ID: b8c6c2905fce

Machine Learning Engineer

Indeed · Saint Louis, MO

Mid-level

2026-04-23

MO 2026-04-23

View full posting on CareerOneStop → ID: 4d67deffd062

(USA) Staff, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-23

AR 2026-04-23

View full posting on CareerOneStop → ID: b8c783501537

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Little Rock, AR

Senior

2026-04-23

AR 2026-04-23

View full posting on CareerOneStop → ID: 88f4e28f161d

Machine Learning Engineer

Indeed · Little Rock, AR

Mid-level

2026-04-23

AR 2026-04-23

View full posting on CareerOneStop → ID: d94fddee36ad

Senior, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-23

AR 2026-04-23

View full posting on CareerOneStop → ID: 41c7cf9af5b2

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Baton Rouge, LA

Senior

2026-04-23

LA 2026-04-23

View full posting on CareerOneStop → ID: 2783ce3fb9ee

Machine Learning Engineer

Indeed · Baton Rouge, LA

Mid-level

2026-04-23

LA 2026-04-23

View full posting on CareerOneStop → ID: 325e5c4bab69

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Jackson, MS

Senior

2026-04-23

MS 2026-04-23

View full posting on CareerOneStop → ID: a8540239933b

Machine Learning Engineer

Indeed · Jackson, MS

Mid-level

2026-04-23

MS 2026-04-23

View full posting on CareerOneStop → ID: 13401d7322b3

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Montgomery, AL

Senior

2026-04-23

AL 2026-04-23

View full posting on CareerOneStop → ID: 8dbd72547ea3

Machine Learning Engineer

Indeed · Huntsville, AL

Mid-level

2026-04-23

AL 2026-04-23

View full posting on CareerOneStop → ID: 166be97e2d08

Data Scientist Analyst OR Senior Data Scientist Analyst, Crop Insurance

Zurich NA · Frankfort, KY

Senior

2026-04-23

KY 2026-04-23

View full posting on CareerOneStop → ID: 449252db4b6e

Machine Learning Engineer

Indeed · Louisville, KY

Mid-level

2026-04-23

KY 2026-04-23

View full posting on CareerOneStop → ID: c4008c409387

Data Scientist III - AMZ9971313

Amazon · Seattle, WA

Mid-level Master's

2026-04-22

WA 2026-04-22

Preferred

Please see job description and the position requirements above.

Responsibilities

Own the data science elements of various products to help with data-based decision making, product performance optimization, and product performance tracking. Work directly with product managers to help drive the design of the product. Work with Technical Product Managers to help drive the build planning. Translate business problems and products into data requirements and metrics. Initiate the design, development, and implementation of scientific analysis projects or deliverables. Own the analysis, modelling, system design, and development of data science solutions for products. Write documents and make presentations that explain model/analysis results to the business. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches. Build consensus on data, metrics, and analysis to drive business and system strategy.
40 hours / week, 8:00am-5:00pm, Salary Range $165,006/year to $215,300/year.
Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit:

View full posting on CareerOneStop → ID: fcdf242c6404

Machine Learning Engineer, (Applied Machine Learning), AI & Data Platforms (AiDP)

Apple · Seattle, WA

Mid-level Doctorate

2026-04-22

WA 2026-04-22

Requirements

Bachelor of Science in Computer Science, Machine Learning, or a related quantitative field or equivalent experience
2+ years of hands-on experience in applied AI/machine learning work in industry or 4+ years of hands on AI research and development experience in academia
Demonstrated expertise in generative AI, computer vision, natural language processing, or general machine learning with a passion for problem solving.

Preferred

MS or Phd in Machine Learning, Natural Language Processing, Computer Vision or related areas strongly preferred
Experience in ML frameworks for training, fine-tuning, and deploying ML/generative models at scale
Proven track record of building large scale, enterprise-grade ML/Gen-AI products in cloud environments (AWS, GCP , Azure) or on-prem infrastructure

Responsibilities

Imagine what you could do here. At Apple, revolutionary ideas have a way of becoming extraordinary products, services, and customer experiences. Join the Ai Data Platform Applied Machine Learning team to pioneer enterprise solutions where generative AI meets Apple's unique commitment to privacy-first innovation. Together, we'll create tools that redefine industries while safeguarding what matters most - our users' trust.
As a pivotal member of Apple's enterprise generative AI efforts, you will help design, build, and evolve models, tools and applications that power high-impact AI experiences across the company. You will contribute to the architecture and optimization of AI/gen AI systems built for high availability, scalability, and reliability, working across backend services and application layers. You would solve AI problems in gen AI Safety, machine translation, content understanding, multi-modality, multi-agent systems, fine tuning and more. Our team designs and implements SOTA AI Models, services, and AI platform components that advance adoption of gen AI at apple. We tackle unique AI challenges in AI Safety, privacy-preserving generations, efficient inference, and multimodal integration, while enabling teams to build on top of our foundations. We deliver production-grade systems and models that meet Apple's rigorous standards for quality, performance, and scalability.

View full posting on CareerOneStop → ID: 41a389766942

ML Engineer - Automated Evaluation and Adversarial Design

Apple · Seattle, WA

Mid-level Master's

2026-04-22

WA 2026-04-22

Requirements

Bachelor's degree in Computer Science, Machine Learning, Statistics, or a related field
4+ years of experience building or significantly extending ML evaluation systems, including designing evaluation benchmarks or quality assessment frameworks including evaluation of sequential or multi-step AI outputs
Experience independently defining evaluation architecture and methodology for AI or ML systems with the ability to design evaluation approaches where the unit of analysis is a conversation or session rather than a single output
Experience designing adversarial or red-teaming test methodologies for ML models or AI-powered features including adversarial scenarios that target failures across multi-turn interactions
Experience with Python and ML frameworks (PyTorch, TensorFlow, or equivalent) in production or near-production settings
Track record of owning technical direction for evaluation efforts across multiple features or product areas

Preferred

Experience evaluating user-facing AI features in consumer applications, with an understanding of how technical metrics connect to user-perceived quality
Familiarity with productivity software or creative tools, with the ability to assess output quality from a user workflow perspective
Experience ensuring alignment between automated and human evaluation methods, including inter-annotator agreement analysis and bias detection
Track record of designing evaluation systems that scale across multiple features or product areas without requiring bespoke solutions for each
Experience evaluating different types of AI systems, including API-based and custom-trained models
Demonstrated ability to communicate evaluation findings and readiness assessments to cross-functional partners
Experience leveraging automation to scale evaluation data generation and analysis
Experience building evaluation pipelines for conversational AI, dialogue systems, or agentic workflows, including turn-level and session-level automated scoring
Familiarity with agent orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen) and observability tooling (LangSmith, Braintrust, Arize), with an understanding of how to instrument and evaluate multi-step agent runs
Experience designing adversarial tests for tool-use reliability, function-calling accuracy, or agent planning quality
Graduate degree in a relevant field

Responsibilities

The Productivity and Machine Learning Evaluation team ensures the quality of AI-powered features across a suite of productivity and creative applications; including Creator Studio, used by hundreds of millions of people. This team serves as the primary evaluation function, providing critical quality signals that directly influence model development decisions and product launches.
This role focuses on building and scaling automated evaluation systems and designing adversarial and stress-testing methodologies across multiple AI features. The work requires a deep understanding of how AI systems fail and how to measure quality rigorously. As features evolve from single-turn interactions into multi-turn, agentic experiences, the evaluation challenge shifts from assessing individual outputs to stress-testing entire conversation flows and agent decision chains. This is an opportunity to shape the evaluation infrastructure that determines whether AI features meet the bar for hundreds of millions of users.
Day-to-day work involves designing, building, and maintaining automated evaluation systems that assess AI feature quality at scale, including multi-turn conversation evaluation and end-to-end agent workflow testing. This includes creating adversarial test suites that probe model weaknesses and running stress tests to ensure features perform under demanding conditions, with particular focus on failure modes that only emerge across extended interactions, such as: context degradation, goal drift, and compounding errors.
Typical deliverables include: evaluation frameworks and rubrics, quality assessment reports, adversarial test case libraries, multi-turn stress-test pipelines, and recommendations on model readiness.

View full posting on CareerOneStop → ID: 3c394469498c

ML Engineer - Evaluation Analysis, Metric and Data Strategy

Apple · Seattle, WA

Mid-level Master's

2026-04-22

WA 2026-04-22

Requirements

Bachelor's degree in Statistics, Data Science, Applied Mathematics, Computer Science, or a related quantitative field
5+ years of experience in applied science, data science, or evaluation research, with a focus on defining and operationalizing quality metrics
Experience with statistical analysis methods including significance testing, sampling design, effect size estimation, and experimental design
Experience working with production user data, understanding its biases and limitations compared to controlled evaluation data, including familiarity with sequential interaction data where context and turn order affect quality assessment
Ability to design evaluation approaches where the unit of analysis is a session or conversation rather than a single model output
Track record of independently designing metrics frameworks and driving data-informed decisions across cross-functional teams
Proficiency in Python (pandas, scipy, scikit-learn) or R for data analysis and visualization

Preferred

Experience designing evaluation or quality metrics for AI-powered or ML-driven features in consumer-facing products
Familiarity with productivity software or creative applications, with an ability to distinguish between technically correct and genuinely useful AI outputs
Experience partnering with engineering or data teams to define data collection requirements and schemas
Track record of translating complex analytical findings into concise recommendations for non-technical decision-makers
Experience evaluating tool-use accuracy, retrieval quality, or function-calling reliability within AI systems
Experience with evaluation methodology including inter-annotator agreement, evaluation bias detection, and dataset representativeness auditing
Familiarity with agentic orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen) and emerging agent interoperability protocols (A2A, MCP), with an understanding of how architectural choices in agent design affect evaluability
Understanding of ML model development processes, with the ability to specify what evaluation signals are useful for model improvement
Experience managing evaluation across multiple features or product areas simultaneously, with systematic rather than ad-hoc approaches
Graduate degree in a relevant quantitative field

Responsibilities

The Productivity and Machine Learning Evaluation team ensures the quality of AI-powered features across a suite of productivity and creative applications; including Creator Studio, used by hundreds of millions of people. This team serves as the primary evaluation function, and its analysis directly informs decisions about model development, feature launches, and product direction.
This role is the analytical core of the team; responsible for making sense of evaluation signals and real-world user behavior. The work involves designing feature-level quality metrics, collaborating with partner teams on data collection strategies, and translating evaluation data into concise, actionable insights that drive decisions. This is an opportunity to define how AI feature quality is measured and to directly shape what gets shipped. As AI features evolve into multi-turn, agentic experiences, this role will define what "quality" means when the unit of evaluation is a conversation, not a single response.
Day-to-day work involves analyzing evaluation results, identifying trends, regressions, and segment-level patterns across multiple AI features. This includes collaborating with partner teams on data collection strategies, ensuring evaluation data is representative of real-world usage, and designing the metrics framework that leadership uses to make decisions on AI features.
Typical deliverables include: feature-level quality metrics and dashboards, evaluation analysis reports, data collection requirements, dataset representativeness audits, multi-turn evaluation frameworks and session-level scoring rubrics, and concise metric summaries for decision-makers.

View full posting on CareerOneStop → ID: bb191e99c6a9

Generative AI Senior Data Scientist

Norstella · Olympia, WA

Senior Master's

2026-04-22

WA 2026-04-22

Requirements

Degree at Masters level or higher in a STEM field such as Math, Physics, Computer Science, Engineering, or equivalent practical experience
Excellent knowledge of python and core data science libraries, and using LLM libraries as part of algorithm design
Project lead experience, managing stakeholders and highly specialized professionals in other non-technical
Excellent technical communication skills when working with a broader development and product team
Knowledge of Scrum, Kanban, and other Agile methodologies, as well as breaking down tasks into Jira tickets

Preferred

Experience with AWS, serverless compute, containerization and storage
Knowledge of the pharmaceutical industry, in particular the stages of pharmaceutical product development and clinical language / ontologies
Ability to rapidly prototype new product ideas with a basic familiarity across the full stack, webapp to database
Experience using external APIs in a production context

Responsibilities

In this role as a Generative AI Senior Data Scientist you will:
Work with our Product leadership within Norstella to define and shape new offerings where agents and assistants can help customers
Manage a team of data scientists and developers to provide Generative AI-enabled API services to the front end dev team
Manage a roadmap of Generative AI work, mixing new product development and enhancements to existing services
Define LLM and Agent architectures suitable to answer complex questions, including via code interpreting, LLM tool use and leveraging secondary data science models
Coach and train a team of data scientists and developers to use these architectures
Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to the data science team on these developments
All other duties, as assigned
*How You'll Succeed
Ultimately our goal is to smooth patient access to life-saving therapies. You will work with R&D pharma specialists to understand a problem which is hindering developing and releasing effective new pharma products which we believe we can help with. After understanding the problem you will conceptualize potential solutions; this will involve breaking down the problem into individual steps, identifying how our existing framework of services can fit in, and what modifications and extensions are necessary for a successful launch. Finally, an overall solution can be packaged together, mixed with classical logic and business rules. As a Senior-level engineer you will be primarily responsible for one major release at a time.
After conceiving potential solution(s), you will research potential packages, LLMs, and approaches, document the high-level tasks in Jira with estimates for time taken for yourself and other data scientists and python developers to implement the solution as a proof-of-concept. You will deliver indicative results starting from test questions into answer datasets for exploration by the broader multi-functional team. You will also perform code reviews with the data science team to examine their implementation and consider ways of strengthening the final codebase and methodology.
After iterating the design with the multi-functional team as part of customer-led product development, you might convert your prototype into a full product. This will involve productionizing code from you and the team to a high standard, containerization, and deployment of the algorithm, usually in AWS ECS, using existing CICD templates. Over time you may revisit this product, re-evaluate its performance, and redesign/improve as required. Historically, if successful, a General Availability launch is typically ~6 months from project start.

View full posting on CareerOneStop → ID: 7b1d2ac94fe7

Senior Data Scientist

Norstella · Olympia, WA

Senior Master's

2026-04-22

WA 2026-04-22

Requirements

5+ years of experience developing AI / ML applications and data driven solutions, preferably in regulated industries (pharma, legal, financial services, or energy)
Graduate degree in Computer Science, Engineering, Statistics or a related quantitative discipline, or equivalent work experience
Substantial depth and breadth in NLP, Deep Learning, Generative AI, LLMs, and other state of the art AI / ML techniques
Deep experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or similar libraries
Expert-level knowledge of LLM APIs (OpenAI, Anthropic Claude) and open-source models (Llama, Mistral)
Deep understanding of CS fundamentals, computational complexity and algorithm design
Experience with building large-scale distributed systems in an agile environment and the ability to build quick prototypes
Excellent knowledge of Python and core data science and AI libraries including Pandas, NumPy, PyTorch, and simila
Experience building or utilizing Model Context Protocol (MCP) servers to bridge models with data tools
Strong background in scalable backend environments (Docker, Kubernetes, AWS/GCP)
Experience moving AI from prototype to production-grade services with monitoring, logging, and rate-limiting
Ability to independently conduct research and develop appropriate algorithmic solutions to complex business problems
Experience mentoring junior team members
Excellent problem solving and communication skills

Preferred

Knowledge of the healthcare / pharma domain and experience with applying AI to healthcare data
Experience with AWS, especially ECS, Bedrock, API Gateway, SageMaker, serverless compute and storage such as S3 and Snowflake
Proficiency with vector databases such as Pinecone, Qdrant, or similar for high-performance retrieval
Experience with RAG patterns, prompt engineering, model fine tuning, and knowledge graphs
Experience with unstructured document processing (legal document analysis, contract management, data retrieval)
Experience with Big Data tools like Apache Spark, Hadoop, or Databricks

Responsibilities

Our dedicated Data Science team is at the forefront of revolutionizing pharma intelligence and how patients gain access to life-saving therapies. Armed with cutting-edge technology and a passion for innovation, we leverage the vast landscape of data to extract actionable insights that drive informed decision making.
Our unique collaborative approach fosters a dynamic synergy between data science and product development. Our deep expertise in machine learning, artificial intelligence, large language models, and generative AI, combined with our domain knowledge, enables us to deliver comprehensive, production-grade AI solutions that empower our clients to stay ahead in a rapidly evolving industry.
In this role as a Senior Data Scientist, you will:
Design and deploy production-ready AI systems that leverage LLMs and advanced ML techniques to solve complex business problems across pharma intelligence
Build and maintain multi-agent systems and agentic orchestration workflows using frameworks like LangChain, LangGraph, or AutoGen to execute autonomous tasks
Develop and optimize Retrieval-Augmented Generation (RAG) pipelines, ensuring high-fidelity context retrieval and vector database management
Implement and extend MCP (Model Context Protocol) servers to allow LLMs to interact safely and efficiently with local and remote data sources
Architect robust, scalable APIs and microservices to serve AI features to end-users with low latency (FastAPI or similar)
Collaborate with product partners and other scientists to identify new opportunities to apply AI / ML to our content and products
Conduct research and identify AI / ML algorithms and methods to solve specific business problems, and deliver these algorithms as microservices in collaboration with content and product engineering teams
Implement rigorous testing and evaluation frameworks for LLM outputs to ensure prompt stability, prevent regressions, and manage hallucination risks
Contribute towards the common data science platform
Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal teams on these developments
All other duties, as assigned

View full posting on CareerOneStop → ID: f86e2dffa9ab

Generative AI Senior Data Scientist

Norstella · Boise, ID

Senior

2026-04-22

ID 2026-04-22

View full posting on CareerOneStop → ID: be77d872abf8

Senior Data Scientist

Norstella · Boise, ID

Senior

2026-04-22

ID 2026-04-22

View full posting on CareerOneStop → ID: 37aa458210c2

Generative AI Senior Data Scientist

Norstella · Salem, OR

Senior

2026-04-22

OR 2026-04-22

View full posting on CareerOneStop → ID: 5ee55d7552d6

Senior Data Scientist

Norstella · Salem, OR

Senior

2026-04-22

OR 2026-04-22

View full posting on CareerOneStop → ID: 94dda8dd0c83

Generative AI Senior Data Scientist

Norstella · Helena, MT

Senior

2026-04-22

MT 2026-04-22

View full posting on CareerOneStop → ID: 5912b02274d1

Senior Data Scientist

Norstella · Helena, MT

Senior

2026-04-22

MT 2026-04-22

View full posting on CareerOneStop → ID: 515d44444424

Generative AI Senior Data Scientist

Norstella · Cheyenne, WY

Senior

2026-04-22

WY 2026-04-22

View full posting on CareerOneStop → ID: 6a863d8c88be

Senior Data Scientist

Norstella · Cheyenne, WY

Senior

2026-04-22

WY 2026-04-22

View full posting on CareerOneStop → ID: 70dbb054e48a

Data Science Intern

University of Utah Health · Salt Lake City, UT

Intern

2026-04-22

UT 2026-04-22

View full posting on CareerOneStop → ID: b4898708d293

Generative AI Senior Data Scientist

Norstella · Salt Lake City, UT

Senior

2026-04-22

UT 2026-04-22

View full posting on CareerOneStop → ID: 9259eeb27c16

Senior Data Scientist

Norstella · Salt Lake City, UT

Senior

2026-04-22

UT 2026-04-22

View full posting on CareerOneStop → ID: aed70bb41d14

Generative AI Senior Data Scientist

Norstella · Carson City, NV

Senior

2026-04-22

NV 2026-04-22

View full posting on CareerOneStop → ID: 538f540947e3

Senior Data Scientist

Norstella · Carson City, NV

Senior

2026-04-22

NV 2026-04-22

View full posting on CareerOneStop → ID: a09fd44536e9

Generative AI Senior Data Scientist

Norstella · Bismarck, ND

Senior

2026-04-22

ND 2026-04-22

View full posting on CareerOneStop → ID: 566166c1aab2

Senior Data Scientist

Norstella · Bismarck, ND

Senior

2026-04-22

ND 2026-04-22

View full posting on CareerOneStop → ID: ec7ef11f4392

Generative AI Senior Data Scientist

Norstella · Pierre, SD

Senior

2026-04-22

SD 2026-04-22

View full posting on CareerOneStop → ID: 7dac5c9cbb44

Senior Data Scientist

Norstella · Pierre, SD

Senior

2026-04-22

SD 2026-04-22

View full posting on CareerOneStop → ID: f6afb9073195

Generative AI Senior Data Scientist

Norstella · Santa Fe, NM

Senior

2026-04-22

NM 2026-04-22

View full posting on CareerOneStop → ID: 44b8062e0f8a

Senior Data Scientist

Norstella · Santa Fe, NM

Senior

2026-04-22

NM 2026-04-22

View full posting on CareerOneStop → ID: 53ef082528c8

Generative AI Senior Data Scientist

Norstella · Lincoln, NE

Senior

2026-04-22

NE 2026-04-22

View full posting on CareerOneStop → ID: 16ebeea708ff

Senior Data Scientist

Norstella · Lincoln, NE

Senior

2026-04-22

NE 2026-04-22

View full posting on CareerOneStop → ID: 8f331792061f

Generative AI Senior Data Scientist

Norstella · Topeka, KS

Senior

2026-04-22

KS 2026-04-22

View full posting on CareerOneStop → ID: 35a562727728

Senior Data Scientist

Norstella · Topeka, KS

Senior

2026-04-22

KS 2026-04-22

View full posting on CareerOneStop → ID: f2932053492f

Generative AI Senior Data Scientist

Norstella · Oklahoma City, OK

Senior

2026-04-22

OK 2026-04-22

View full posting on CareerOneStop → ID: 88c4b129367c

Senior Data Scientist

Norstella · Oklahoma City, OK

Senior

2026-04-22

OK 2026-04-22

View full posting on CareerOneStop → ID: 699dd67e5093

Generative AI Senior Data Scientist

Norstella · Des Moines, IA

Senior

2026-04-22

IA 2026-04-22

View full posting on CareerOneStop → ID: 0982ac02223b

Senior Data Scientist

Norstella · Des Moines, IA

Senior

2026-04-22

IA 2026-04-22

View full posting on CareerOneStop → ID: 88338b43cf6c

DATA SCIENTIST

State of Arkansas · Little Rock, AR

Mid-level

2026-04-22

AR 2026-04-22

View full posting on CareerOneStop → ID: fa846a23f9d3

Generative AI Senior Data Scientist

Norstella · Little Rock, AR

Senior

2026-04-22

AR 2026-04-22

View full posting on CareerOneStop → ID: aaddc9238011

Principal, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-22

AR 2026-04-22

View full posting on CareerOneStop → ID: 139c1bddb3b6

Senior Data Scientist

Norstella · Little Rock, AR

Senior

2026-04-22

AR 2026-04-22

View full posting on CareerOneStop → ID: d0f3ff9e1053

Staff, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-22

AR 2026-04-22

View full posting on CareerOneStop → ID: 54641f190f1e

Generative AI Senior Data Scientist

Norstella · Baton Rouge, LA

Senior

2026-04-22

LA 2026-04-22

View full posting on CareerOneStop → ID: 70bfaf985201

Senior Data Scientist

Norstella · Baton Rouge, LA

Senior

2026-04-22

LA 2026-04-22

View full posting on CareerOneStop → ID: d969392b869a

Generative AI Senior Data Scientist

Norstella · Jackson, MS

Senior

2026-04-22

MS 2026-04-22

View full posting on CareerOneStop → ID: 4f3e4eb634e9

Senior Data Scientist

Norstella · Jackson, MS

Senior

2026-04-22

MS 2026-04-22

View full posting on CareerOneStop → ID: b8191d7682ea

Generative AI Senior Data Scientist

Norstella · Montgomery, AL

Senior

2026-04-22

AL 2026-04-22

View full posting on CareerOneStop → ID: cc8b9dba7d67

Senior Data Scientist

Norstella · Montgomery, AL

Senior

2026-04-22

AL 2026-04-22

View full posting on CareerOneStop → ID: 3ceafcc87fe2

Generative AI Senior Data Scientist

Norstella · Frankfort, KY

Senior

2026-04-22

KY 2026-04-22

View full posting on CareerOneStop → ID: fdfb3d682166

Senior Data Scientist

Norstella · Frankfort, KY

Senior

2026-04-22

KY 2026-04-22

View full posting on CareerOneStop → ID: a1aced0cb3a1

Data Scientist II, Amazon Stores Finance Science

Amazon · Bellevue, WA

Mid-level Master's

2026-04-21

WA 2026-04-21

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Experience applying theoretical models in an applied environment
Bachelor's degree

Preferred

Experience in a ML or data scientist role with a large technology company
Experience working on multi-team, cross-disciplinary projects
Experience effectively communicating complex concepts through written and verbal communication
Master's degree
Experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems

Responsibilities

Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry standard ML models
Working with technical and non-technical stakeholders across every step of science project life cycle
Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models
Innovating by adapting new modeling techniques and procedures
Presenting research results to our internal research community

View full posting on CareerOneStop → ID: 1e66715e63dc

Product Test Engineer - Machine Learning Hardware, RRL Technical Engineering, RRL Technical Engineering

Amazon · Florence, KY

Mid-level

2026-04-21

KY 2026-04-21

View full posting on CareerOneStop → ID: 73827fd56bcb

Senior Data Scientist

Humana, Inc. · Louisville, KY

Senior

2026-04-21

KY 2026-04-21

View full posting on CareerOneStop → ID: 4ab583c4aa20

Principal Machine Learning Data Scientist, Gen AI

Xometry · Lexington, KY

Senior

2026-04-20

KY 2026-04-20

View full posting on CareerOneStop → ID: 2b0c82530fcb

Senior Data Scientist, Cost Prediction

Xometry · Lexington, KY

Senior

2026-04-20

KY 2026-04-20

View full posting on CareerOneStop → ID: ddad29bed86c

Senior Data Scientist, Costing

Xometry · Lexington, KY

Senior

2026-04-20

KY 2026-04-20

View full posting on CareerOneStop → ID: 5c96916022a9

Senior Machine Learning Engineer

Xometry · Lexington, KY

Senior

2026-04-20

KY 2026-04-20

View full posting on CareerOneStop → ID: 84fba3cebc23

Staff Machine Learning Engineer - Generative AI

Xometry · Lexington, KY

Senior

2026-04-20

KY 2026-04-20

View full posting on CareerOneStop → ID: 02628ac4152c

Sr Data Scientist

Micron Technology, Inc. · Boise, ID

Senior

2026-04-19

ID 2026-04-19

View full posting on CareerOneStop → ID: 137b8a6a623c

Staff Product Data Scientist, Ads Privacy and Safety

Google · Kirkland, WA

Senior Master's

2026-04-18

WA 2026-04-18

Requirements

Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 8 years of experience with a Master's degree.

Preferred

Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
Familiarity with global privacy regulations (e.g., General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), Digital Markets Act (DMA)) and their implications relevant to technology companies.
Knowledge of financial forecasting, scenario analysis and risk assessment for Ads.

Responsibilities

The Ads Privacy and Safety team (APaS) is dedicated to fostering trust and transparency within the Google Ads ecosystem. This involves ensuring safety and respect for users, advertisers, and publishers by combating invalid traffic, promoting privacy-respecting business generation practices that empower user control, and advancing content understanding through human and machine intelligence.
The APaS Data Science team plays a crucial role in safeguarding the integrity of Google's advertising platform. By focusing on data-driven objectivity, accountability, and user-centricity, this team develops unbiased frameworks to measure business health and deliver impact assessments across key areas like risk, business, and user trust. They proactively counter threats by enabling precise measurement and ensuring the focus remains on the right problems. Through close partnerships across APaS, the team provides continuous measurement and influences strategic decisions with objective insights.
As a Senior Data Scientist, you will join our Ads privacy and regulations team. In this crucial role, you will drive data-driven decision-making to ensure regulatory compliance and unlock growth opportunities within Google Ads, safeguarding billions in business while enhancing user trust. You will be a key player in navigating the complex landscape of privacy laws and regulations, developing quantitative models and frameworks that enable Google Ads to adapt and grow. You will be responsible for analyzing the impact of evolving regulations, quantifying risks and opportunities, and generating actionable insights that inform product development, policy adjustments, and using user preference and consented signals effectively for Ads targeting.The US base salary range for this full-time position is $192,000-$278,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Partner with cross-functional teams and deliver data driven insights to stakeholders across Ads, focusing on advertiser, publisher, and user trust and experience.
Develop and implement quantitative frameworks to assess the impact of Ads safety, traffic quality, user privacy and regulatory compliance on Ads business, user experience, and product capabilities.
Identify areas for optimization in response to evolving trends in the Ads industry and develop models to improve product features against business impact and new threats.
Build and automate reports, iteratively build and prototype dashboards to provide insights at scale, solving for investigative need.
Deliver effective presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: 0ee7a56a7c38

Senior Data Scientist

Fortive Corporation · Everett, WA

Senior Doctorate

2026-04-18

WA 2026-04-18

Requirements

Hold a bachelor's degree (or its equivalent) in computer-science/information-theory/language-technologies or a related fields
Lead end-to-end data science projects, from problem definition and data collection to model development and deployment.
Design and develop machine learning models and algorithms to analyze large, complex datasets and extract meaningful insights.
Collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions.
Explore and implement advanced statistical techniques to uncover trends, patterns, and correlations in data.
Develop predictive models and forecasting algorithms to support decision-making and drive business growth.
Evaluate model performance and make recommendations for model improvements and optimizations.
Stay updated on the latest developments in data science, machine learning, and AI technologies, and identify opportunities for innovation and improvement.
Mentor junior team members and provide technical guidance and support as needed.

Preferred

Master or PHD in computer-science/ information-theory/ language-technologies or related fields
Proven track record of success in applying data science techniques to real-world business problems.
Expertise in programming languages such as Python, R, or SQL, and familiarity with data manipulation and visualization libraries (e.g., pandas, matplotlib, seaborn).
Strong knowledge of machine learning algorithms, deep learning techniques, and statistical modeling.
Experience with big data technologies and platforms (e.g., Hadoop, Spark) and cloud computing services (e.g., AWS, Azure, GCP).
Excellent analytical and problem-solving skills, with the ability to think critically and creatively to solve complex problems.
Effective communication and collaboration skills, with the ability to present technical concepts to non-technical stakeholders.
Proven leadership experience, with the ability to lead and mentor a team of data scientists.
*Fortive Corporation Overview
Fortive's essential technology makes the world safer and more productive. We accelerate transformation in high-impact fields like workplace safety, build environments, and healthcare.
We are a global industrial technology innovator with a startup spirit. Our forward-looking companies lead the way in healthcare sterilization, industrial safety, predictive maintenance, and other mission-critical solutions. We're a force for progress, working alongside our customers and partners to solve challenges on a global scale, from workplace safety in the most demanding conditions to advanced technologies that help providers focus on exceptional patient care.
We are a diverse team 10,000 strong, united by a dynamic, inclusive culture and energized by limitless learning and growth. We use the proven Fortive Business System (FBS) to accelerate our positive impact.
At Fortive, we believe in you. We believe in your potential-your ability to learn, grow, and make a difference.
At Fortive, we believe in us. We believe in the power of people working together to solve problems no one could solve alone.
At Fortive, we believe in growth. We're honest about what's working and what isn't, and we never stop improving and innovating.
Fortive: For you, for us, for growth.
This position is also eligible for bonus as part of the total compensation package.

View full posting on CareerOneStop → ID: 5e5bc337f469

2026 Fall Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning) - United States, PhD Student Science Recruiting

Amazon · Corvallis, OR

Intern

2026-04-18

OR 2026-04-18

View full posting on CareerOneStop → ID: ebbc47165bcb

(USA) Distinguished, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-18

AR 2026-04-18

View full posting on CareerOneStop → ID: 50beb9123f89

(USA) Senior Manager, Data Science

Walmart · Bentonville, AR

Manager

2026-04-18

AR 2026-04-18

View full posting on CareerOneStop → ID: 2fcc6e13bef6

Senior Manager, Data Science - Merchandising Analytics

Walmart · Bentonville, AR

Manager

2026-04-17

AR 2026-04-17

View full posting on CareerOneStop → ID: 6c63b139c5dd

Staff AI/ML Engineer, Developer Productivity

General Motors · Olympia, WA

Senior

2026-04-16

WA 2026-04-16

Requirements

5+ years of experience designing,buildingandoperatingproduction systems at scale in the cloud
BachelorsDegree in Computer Scienceor related field or equivalent work experience
Experience designing highly scalable, reliable, and maintainable services
Experience writing in Go, Python, or other languages at production scale
Understanding of Unix/Linux, SSH, and networking fundamentals
Attention to detail, and a desire to improve processes and systems around you
Ability to lead and influence others, both internal and external to the team
Ability to research, document, communicate, and defend proposals, and provide and take critical feedback
Ability to effectively make trade-offs and communicate the reasoning
Ability to manage competing priorities, focus on shipping, and work effectively under pressure
Passion for mentoring and growing junior engineers
Passion for self-driving technology and its potential impact on the world

Preferred

Demonstratedapplication ofLLMs, skills, and MCPstocoding& review workflows
Experience working with GCP
Experience working with Docker and Kubernetes
Experience owning or contributing to Open-Source projects
*Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.
The salary range for this role: is $180,000 to $284,000. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

Responsibilities

We are looking for a Staff Engineer with an extensive engineering background, experience using a variety of developer tools and technologies, and who is passionate about developer productivity. As a leader on this team, we are looking for someone who cares deeply about the technical development of other engineers on the team and can effectively balance the needs and priorities of the business, our users, and the growth of our engineers.
The way this engineer will deliver impact may vary depending on the situation, but they will be expected to be able to identify how they can best have impact with minimal guidance.
The AV Developer Tools team owns AI-native tools and services that enable others to deploy consistent and secure agentic workflows with visibility into their usage, both hosted and on-device. We are part of the AI Cloud and Developer Productivity organization and own building blocks that allow customers to easily instrument their products to debug, optimize, reach, and maintain production level reliability and availability. This includes setting best practices and providing opinionated drop-in libraries and recommendations for service instrumentation. Our goal is to accelerate AV development by supporting developer workflows for performance and observability into their systems.
*What You'll Do (Responsibilities)
Identifyengineering pain points and propose/design/implement solutions that are reliable, scalable, and maintainable
Influence the team's technical roadmap
Evaluate new tools and technologies throughPoCs
Ship improvements to our AV development toolchains and services which have a measurable and direct impact on engineering productivity and our core company metrics
Drive software engineering best practices within your team, and create tooling which encourages these
Help steer the engineering culture on the team
Guide the team to find the right balance between delivering impact and addressing technical debt
Mentor and grow engineers on the team
Set the example forhigh levelsof accountability
Execute and deliver impact both individually and through the team
Set strong boundaries when selecting external requests and pushing back on requests that do not align with our team vision

View full posting on CareerOneStop → ID: 912d269d60fb

Machine Learning Engineer

Indeed · Portland, OR

Mid-level Master's

2026-04-16

WA 2026-04-16

Responsibilities

The Machine Learning Engineer I role partners closely with business partners across various functions to help execute strategic initiatives that increase revenue, drive operational scale, and improve efficiency for continuous growth. As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source packages and research publications, and creatively adapt models for solving business problems across Indeed.
Work spans classical ML through LLM systems. You improve search and retrieval quality using real user signals. Execution includes experiments, iteration, and production reliability at scale. You collaborate with engineers, data scientists, and product teams to define problems, test approaches, and ship measurable improvements.
Build AI/ML systems for search, ranking, and recommendations
Develop LLM retrieval and generation workflows
Improve search and ranking relevance
Design metrics and run experiments
Monitor model quality, latency, and cost
Debug data, models, and system issues
Build training, inference, and eval pipelines
*Skills/Competencies
Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 2 years of related experience; or an advanced degree without experience
Experience building ML models in Python; solid software engineering and algorithms fundamentals
Experience developing backend services in Java/Kotlin for ML-driven systems and features
Experience writing clean, testable, and maintainable production code
Experience working with structured and unstructured data, including SQL for large-scale data querying, and building scalable data pipelines and features from data
Experience integrating ML models into search systems using engines such as OpenSearch or similar, with familiarity in container orchestration for deployment with senior guidance
Excellent understanding of model evaluation techniques, feature engineering, experiment design, and familiarity with LLM systems (RAG, embeddings, output evaluation)

View full posting on CareerOneStop → ID: d701d3f0cddb

Machine Learning Engineer

Indeed · Boise, ID

Mid-level

2026-04-16

ID 2026-04-16

View full posting on CareerOneStop → ID: 726d72daf191

Machine Learning Engineer

Indeed · Helena, MT

Mid-level

2026-04-16

MT 2026-04-16

View full posting on CareerOneStop → ID: c74d033d23de

Machine Learning Engineer

Indeed · Cheyenne, WY

Mid-level

2026-04-16

WY 2026-04-16

View full posting on CareerOneStop → ID: 4851d2e89227

Machine Learning Engineer

Indeed · Las Vegas, NV

Mid-level

2026-04-16

NV 2026-04-16

View full posting on CareerOneStop → ID: 2f62e69214a8

Machine Learning Engineer

Indeed · Bismarck, ND

Mid-level

2026-04-16

ND 2026-04-16

View full posting on CareerOneStop → ID: 536de2c96ad8

Machine Learning Engineer

Indeed · Sioux Falls, SD

Mid-level

2026-04-16

SD 2026-04-16

View full posting on CareerOneStop → ID: 37b55b9d5b9b

Machine Learning Engineer

Indeed · Albuquerque, NM

Mid-level

2026-04-16

NM 2026-04-16

View full posting on CareerOneStop → ID: 4e75a8e26fb2

Machine Learning Engineer

Indeed · Omaha, NE

Mid-level

2026-04-16

NE 2026-04-16

View full posting on CareerOneStop → ID: 36ed73aab38a

Machine Learning Engineer

Indeed · Kansas City, KS

Mid-level

2026-04-16

KS 2026-04-16

View full posting on CareerOneStop → ID: cb7b5340e364

Machine Learning Engineer

Indeed · Oklahoma City, OK

Mid-level

2026-04-16

OK 2026-04-16

View full posting on CareerOneStop → ID: 9d992ad35aad

Machine Learning Engineer

Indeed · Des Moines, IA

Mid-level

2026-04-16

IA 2026-04-16

View full posting on CareerOneStop → ID: 0d08f3956d40

Data Scientist

Arkansas Employer · Little Rock, AR

Mid-level

2026-04-16

AR 2026-04-16

View full posting on CareerOneStop → ID: 644fed4e1271

Director, Data Science - Earnings Innovation & Automation

Walmart · Bentonville, AR

Director

2026-04-16

AR 2026-04-16

View full posting on CareerOneStop → ID: 2f0ec7e09ab8

Machine Learning Engineer

Indeed · Little Rock, AR

Mid-level

2026-04-16

AR 2026-04-16

View full posting on CareerOneStop → ID: a4ba4396f97f

Machine Learning Engineer

Indeed · Baton Rouge, LA

Mid-level

2026-04-16

LA 2026-04-16

View full posting on CareerOneStop → ID: e472d7d36246

Machine Learning Engineer

Indeed · Jackson, MS

Mid-level

2026-04-16

MS 2026-04-16

View full posting on CareerOneStop → ID: 10894189e6d9

Machine Learning Engineer

Indeed · Huntsville, AL

Mid-level

2026-04-16

AL 2026-04-16

View full posting on CareerOneStop → ID: 2e06bb1e0425

Machine Learning Engineer

Indeed · Louisville, KY

Mid-level

2026-04-16

KY 2026-04-16

View full posting on CareerOneStop → ID: 196d7e0f8820

Data Scientist I, Customer Delivery Excellence Science

Amazon · Bellevue, WA

Entry-level

2026-04-15

WA 2026-04-15

View full posting on CareerOneStop → ID: d79a1f5daed0

Senior Data Scientist, Product, Ads Privacy and Safety

Google · Kirkland, WA

Senior Master's

2026-04-15

WA 2026-04-15

Requirements

Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years of experience with a Master's degree.

Preferred

Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
Familiarity with global privacy regulations (e.g., General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), Digital Markets Act (DMA)) and their implications relevant to technology companies.
Knowledge of financial forecasting, scenario analysis and risk assessment for Ads.

Responsibilities

The Ads Privacy and Safety team (APaS) is dedicated to fostering trust and transparency within the Google Ads ecosystem. This involves ensuring safety and respect for users, advertisers, and publishers by combating invalid traffic, promoting privacy-respecting business generation practices that empower user control, and advancing content understanding through human and machine intelligence.
The APaS Data Science team plays a crucial role in safeguarding the integrity of Google's advertising platform. By focusing on data-driven objectivity, accountability, and user-centricity, this team develops unbiased frameworks to measure business health and deliver impact assessments across key areas like risk, business, and user trust. They proactively counter threats by enabling precise measurement and ensuring the focus remains on the right problems. Through close partnerships across APaS, the team provides continuous measurement and influences strategic decisions with objective insights.
As a Senior Data Scientist, you will join our Ads privacy and regulations team. In this crucial role, you will drive data-driven decision-making to ensure regulatory compliance and unlock growth opportunities within Google Ads, safeguarding billions in business while enhancing user trust. You will be a key player in navigating the complex landscape of privacy laws and regulations, developing quantitative models and frameworks that enable Google Ads to adapt and grow. You will be responsible for analyzing the impact of evolving regulations, quantifying risks and opportunities, and generating actionable insights that inform product development, policy adjustments, and using user preference and consented signals effectively for Ads targeting.
The US base salary range for this full-time position is $163,000-$237,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
Partner with cross-functional teams and deliver data driven insights to stakeholders across Ads, focusing on advertiser, publisher, and user trust and experience.
Develop and implement quantitative frameworks to assess the impact of Ads safety, traffic quality, user privacy and regulatory compliance on Ads business, user experience, and product capabilities.
Identify areas for optimization in response to evolving trends in the Ads industry and develop models to improve product features against business impact and new threats.
Build and automate reports, iteratively build and prototype dashboards to provide insights at scale, solving for analytical need.
Deliver effective presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

View full posting on CareerOneStop → ID: f1f3b5414ab0

SR DATA SCIENTIST, SMAI OI

Micron Technology, Inc. · Boise, ID

Senior

2026-04-15

ID 2026-04-15

View full posting on CareerOneStop → ID: 534d35771aaa

(USA) Senior Manager, Data Science- Supply Chain Strategy

Walmart · Bentonville, AR

Manager

2026-04-15

AR 2026-04-15

View full posting on CareerOneStop → ID: 9e46935c6b8e

Staff Machine Learning Engineer, Inference Team

Google · Kirkland, WA

Senior

2026-04-14

WA 2026-04-14

View full posting on CareerOneStop → ID: 2f047f82d60d

Senior Data Scientist III - Agentic AI

RELX INC · Olympia, WA

Senior

2026-04-14

WA 2026-04-14

View full posting on CareerOneStop → ID: 347fc8c94d95

Senior Data Scientist

FTV Employment Services LLC · Everett, WA

Senior

2026-04-14

WA 2026-04-14

View full posting on CareerOneStop → ID: 528d29f7bdfa

(USA) Senior, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-14

AR 2026-04-14

View full posting on CareerOneStop → ID: 205fc284e06f

Senior, Data Scientist - Merchandising Analytics (Member and Insights)

Walmart · Bentonville, AR

Senior

2026-04-14

AR 2026-04-14

View full posting on CareerOneStop → ID: a3eb69a15e1a

Data Science Intern

Western Ecosystems Technology, Inc. · Laramie, WY

Intern

2026-04-12

WY 2026-04-12

View full posting on CareerOneStop → ID: d6df7f4d4c1c

Senior AI/ML Engineer, Validation Strategy & Test Architecture

Micron Technology, Inc. · Boise, ID

Senior

2026-04-11

ID 2026-04-11

View full posting on CareerOneStop → ID: 3ad8641aa227

Staff Data Scientist, Agentic Platform

Micron Technology, Inc. · Boise, ID

Senior

2026-04-11

ID 2026-04-11

View full posting on CareerOneStop → ID: a7a48ffc2612

(USA) Senior Manager, Data Science - Supply Chain Strategy

Walmart · Bentonville, AR

Manager

2026-04-11

AR 2026-04-11

View full posting on CareerOneStop → ID: 46ea34a7bb22

(USA) Staff, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-11

AR 2026-04-11

View full posting on CareerOneStop → ID: 4d342109aeac

Staff, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-11

AR 2026-04-11

View full posting on CareerOneStop → ID: d5eb46c0e0a0

Staff, Data Scientist - Experimentation & Measurement

Walmart · Bentonville, AR

Senior

2026-04-11

AR 2026-04-11

View full posting on CareerOneStop → ID: 8618ce82a280

Principal AI/ML Engineer, Validation Strategy & Test Architecture

Micron Technology, Inc. · Boise, ID

Senior

2026-04-10

ID 2026-04-10

View full posting on CareerOneStop → ID: d97a0f919ae9

Senior Staff Software Engineer, Machine Learning, ML Training

Google · Kirkland, WA

Senior

2026-04-09

WA 2026-04-09

View full posting on CareerOneStop → ID: 88fce94b9ec9

Data Scientist (5190)

SMX · Olympia, WA

Mid-level

2026-04-09

WA 2026-04-09

View full posting on CareerOneStop → ID: 971cb7d256a5

Data Scientist (5190)

SMX · Boise, ID

Mid-level

2026-04-09

ID 2026-04-09

View full posting on CareerOneStop → ID: 490e261ca5f6

Data Scientist (5190)

SMX · Salem, OR

Mid-level

2026-04-09

OR 2026-04-09

View full posting on CareerOneStop → ID: e0b698b05c94

Data Scientist (5190)

SMX · Helena, MT

Mid-level

2026-04-09

MT 2026-04-09

View full posting on CareerOneStop → ID: 19a9ba327f86

Data Scientist (5190)

SMX · Cheyenne, WY

Mid-level

2026-04-09

WY 2026-04-09

View full posting on CareerOneStop → ID: 5d2c8beb3642

Data Scientist (5190)

SMX · Carson City, NV

Mid-level

2026-04-09

NV 2026-04-09

View full posting on CareerOneStop → ID: 111702713c06

Data Scientist (5190)

SMX · Bismarck, ND

Mid-level

2026-04-09

ND 2026-04-09

View full posting on CareerOneStop → ID: 5cc7ce271681

Data Scientist (5190)

SMX · Pierre, SD

Mid-level

2026-04-09

SD 2026-04-09

View full posting on CareerOneStop → ID: e18a6a9b8988

Data Scientist (5190)

SMX · Santa Fe, NM

Mid-level

2026-04-09

NM 2026-04-09

View full posting on CareerOneStop → ID: cf145228080a

Data Scientist (5190)

SMX · Lincoln, NE

Mid-level

2026-04-09

NE 2026-04-09

View full posting on CareerOneStop → ID: 20117eb9fc5b

Data Scientist (5190)

SMX · Topeka, KS

Mid-level

2026-04-09

KS 2026-04-09

View full posting on CareerOneStop → ID: 932b148e006f

Data Scientist (5190)

SMX · Oklahoma City, OK

Mid-level

2026-04-09

OK 2026-04-09

View full posting on CareerOneStop → ID: a5e1b3817825

Data Scientist (5190)

SMX · Little Rock, AR

Mid-level

2026-04-09

AR 2026-04-09

View full posting on CareerOneStop → ID: 4ff3ef55c1c5

Data Scientist (5190)

SMX · Baton Rouge, LA

Mid-level

2026-04-09

LA 2026-04-09

View full posting on CareerOneStop → ID: 341157ef87bd

Data Scientist (5190)

SMX · Jackson, MS

Mid-level

2026-04-09

MS 2026-04-09

View full posting on CareerOneStop → ID: 1e9adb78fc9f

Data Scientist (5190)

SMX · Montgomery, AL

Mid-level

2026-04-09

AL 2026-04-09

View full posting on CareerOneStop → ID: ffb8c9b0b217

Data Scientist (Starlink)

SpaceX · Redmond, WA

Mid-level

2026-04-08

WA 2026-04-08

View full posting on CareerOneStop → ID: c1c722066c0b

Staff Software Engineer, Machine Learning Compilers, Edge TPU

Google · Kirkland, WA

Senior

2026-04-08

WA 2026-04-08

View full posting on CareerOneStop → ID: 596d26b8b420

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Olympia, WA

Mid-level

2026-04-08

WA 2026-04-08

View full posting on CareerOneStop → ID: eb24ade14ae5

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Boise, ID

Mid-level

2026-04-08

ID 2026-04-08

View full posting on CareerOneStop → ID: c4107b6525e4

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Salem, OR

Mid-level

2026-04-08

OR 2026-04-08

View full posting on CareerOneStop → ID: 3dc638905f64

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Helena, MT

Mid-level

2026-04-08

MT 2026-04-08

View full posting on CareerOneStop → ID: 2b439f6e6c88

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Cheyenne, WY

Mid-level

2026-04-08

WY 2026-04-08

View full posting on CareerOneStop → ID: a8f4331edeeb

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Carson City, NV

Mid-level

2026-04-08

NV 2026-04-08

View full posting on CareerOneStop → ID: 3f1d0dcd2018

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Bismarck, ND

Mid-level

2026-04-08

ND 2026-04-08

View full posting on CareerOneStop → ID: 21504f2294d4

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Pierre, SD

Mid-level

2026-04-08

SD 2026-04-08

View full posting on CareerOneStop → ID: 2dfd23e9b681

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Santa Fe, NM

Mid-level

2026-04-08

NM 2026-04-08

View full posting on CareerOneStop → ID: 312f78d1f5d6

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Lincoln, NE

Mid-level

2026-04-08

NE 2026-04-08

View full posting on CareerOneStop → ID: a6b8fcd7cdd7

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Topeka, KS

Mid-level

2026-04-08

KS 2026-04-08

View full posting on CareerOneStop → ID: d5ac1387d33b

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Oklahoma City, OK

Mid-level

2026-04-08

OK 2026-04-08

View full posting on CareerOneStop → ID: 4e3555ad57bb

(USA) Principal, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-08

AR 2026-04-08

View full posting on CareerOneStop → ID: 12391bdde80b

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Little Rock, AR

Mid-level

2026-04-08

AR 2026-04-08

View full posting on CareerOneStop → ID: e4f90219b6e8

Senior, Data Scientist - Inventory Flow Analytics, CVP Analytics Root Cause and Optimization

Walmart · Bentonville, AR

Senior

2026-04-08

AR 2026-04-08

View full posting on CareerOneStop → ID: 946e95a176c9

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Baton Rouge, LA

Mid-level

2026-04-08

LA 2026-04-08

View full posting on CareerOneStop → ID: 23b54332db29

Operations Research Analyst / Data Scientist (Remote)

GovCIO · Jackson, MS

Mid-level

2026-04-08

MS 2026-04-08

View full posting on CareerOneStop → ID: 9b1e91705467

Data Scientist II

Indeed · Portland, OR

Mid-level

2026-04-07

WA 2026-04-07

View full posting on CareerOneStop → ID: c0e919f02e1c

Senior Machine Learning Engineer, MLOps West Coast

Autodesk · Portland, OR

Senior

2026-04-07

WA 2026-04-07

View full posting on CareerOneStop → ID: 6e350dd7cc13

Data Scientist II

Indeed · Boise, ID

Mid-level

2026-04-07

ID 2026-04-07

View full posting on CareerOneStop → ID: d8b2b4e45cad

Data Scientist II

Indeed · Helena, MT

Mid-level

2026-04-07

MT 2026-04-07

View full posting on CareerOneStop → ID: 8104ba673ebc

Data Scientist II

Indeed · Cheyenne, WY

Mid-level

2026-04-07

WY 2026-04-07

View full posting on CareerOneStop → ID: 7dabd5f8fd84

Data Scientist II

Indeed · Las Vegas, NV

Mid-level

2026-04-07

NV 2026-04-07

View full posting on CareerOneStop → ID: e4a1ad55d3bf

Data Scientist II

Indeed · Bismarck, ND

Mid-level

2026-04-07

ND 2026-04-07

View full posting on CareerOneStop → ID: 97bc34c5a581

Data Scientist II

Indeed · Sioux Falls, SD

Mid-level

2026-04-07

SD 2026-04-07

View full posting on CareerOneStop → ID: de2a24ac78b7

Data Scientist II

Indeed · Albuquerque, NM

Mid-level

2026-04-07

NM 2026-04-07

View full posting on CareerOneStop → ID: a3fa3e1eea5a

Data Scientist II

Indeed · Omaha, NE

Mid-level

2026-04-07

NE 2026-04-07

View full posting on CareerOneStop → ID: f05e6438bd3a

Data Scientist II

Indeed · Kansas City, KS

Mid-level

2026-04-07

KS 2026-04-07

View full posting on CareerOneStop → ID: 8fa15f7a5940

Data Scientist II

Indeed · Oklahoma City, OK

Mid-level

2026-04-07

OK 2026-04-07

View full posting on CareerOneStop → ID: f9cb2291bac3

(USA) Senior, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-07

AR 2026-04-07

View full posting on CareerOneStop → ID: 066bd154c2f4

Data Scientist II

Indeed · Little Rock, AR

Mid-level

2026-04-07

AR 2026-04-07

View full posting on CareerOneStop → ID: 117d4b68c4c2

Data Scientist II

Indeed · Baton Rouge, LA

Mid-level

2026-04-07

LA 2026-04-07

View full posting on CareerOneStop → ID: 478f1ef8ad42

Data Scientist II

Indeed · Jackson, MS

Mid-level

2026-04-07

MS 2026-04-07

View full posting on CareerOneStop → ID: 62281102fe7b

Senior Data Scientist, Amazon Stores Finance Science, Amazon Stores Finance Science

Amazon · Bellevue, WA

Senior Master's

2026-04-05

WA 2026-04-05

Requirements

5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
4+ years of data scientist experience
Experience with statistical models e.g. multinomial logistic regression
Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
Experience managing data pipelines

Preferred

Experience as a leader and mentor on a data science team
Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)
Master's degree
Experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems

Responsibilities

Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry standard ML models
Working with technical and non-technical stakeholders across every step of science project life cycle
Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models
Innovating by adapting new modeling techniques and procedures
Presenting research results to our internal research community

View full posting on CareerOneStop → ID: d73d393e6308

Member of Technical Staff - Data Scientist

Microsoft Corporation · Redmond, WA

Senior Doctorate

2026-04-04

WA 2026-04-04

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.

Preferred

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Responsibilities

Drive product insights, opportunity analysis, and track metrics to support eRorts across Microsoft Copilot.
Drive new ways of instrumentingand measuring impactto evaluate new feature performance through experimentation.
Define metrics and build basic data pipelines to enable A|B experimentation for new features and mitigating abusive users.
Hands-on analysis of large volumes of telemetry data using various algorithms and tools including your own
Articulate insights, storyboard with data and communicate to influence leadership and other key decision makers
Find a path to get things done despite roadblocks to get your work into the hands of users quickly and iteratively.
Enjoy working in a fast-paced, design-driven, product development cycle.
Work collaboratively with our engineers, Product Managers, and marketing to take ambiguous projects that drive user growth, engagement, and retention. This includes identifying market opportunities, optimizing app flows and improvingproduct features and proposing innovation solutions based on data.
Embody ourCultureandValues.

View full posting on CareerOneStop → ID: 67a405a6e916

Staff Machine Learning Engineer

Indeed · Portland, OR

Senior Doctorate

2026-04-04

WA 2026-04-04

Responsibilities

As a Machine Learning Engineer III you will be a team lead on the Marketplace Efficiency - Job Reach team. Your team will be responsible for maintaining and improving a healthy marketplace for job advertisers. You will own one of the team's major workstreams, help drive technical direction for the team, and guide other members of the team to achieve product/technical goals. On a daily basis, you will explore data and formulate problem statements, develop and deploy predictive models while monitoring them in production, execute high-quality experiments, and guide the team on the same. Additionally, you will partner with cross-functional teams, evangelize your team's work, and stay updated with the latest advancements in the field.
Partner with cross-functional teams to enhance and optimize search algorithms for improved accuracy, relevance, and overall user experience.
Experiment with Proof of Concept Machine Learning model improvements, scale them to production, and run iterative A/B experiments to improve our matching technology while partnering with other teams
Define and clarify project priorities, deliverables, and success criteria in partnership with cross-functional teams.
Act as a bridge between technical and non-technical collaborators, facilitating effective communication and comprehension of project goals and outcomes.
Mentor and grow other software engineers and Machine Learning Engineers across teams
Break down larger Machine Learning initiatives into pieces that deliver incremental business value and guide the team through implementing them
Represent Indeed at major Machine Learning conferences, such as Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the International Conference on Learning Representations (ICLR).
*Skills/Competencies
Requires a minimum of 8 years of related experience with a Bachelor's degree in Computer Science, Mathematics, or Statistics; or 6 years and a Master's degree; or a PhD with 3 years experience
Prior success in deploying impactful Machine Learning solutions to large-scale production systems, while partnering across teams
Solid knowledge of data structures and algorithms
Sense of ownership and accountability as a key contributor in the technical and product domains
Knowledge and practical experience working on Deep Learning Libraries (like Torch, Tensorflow, etc.)
Excellent written and verbal communication in English, effective with technical and business audiences

View full posting on CareerOneStop → ID: 4beecaaae076

Staff Machine Learning Engineer

Indeed · Boise, ID

Senior

2026-04-04

ID 2026-04-04

View full posting on CareerOneStop → ID: fd1b19c54d86

Staff Machine Learning Engineer

Indeed · Helena, MT

Senior

2026-04-04

MT 2026-04-04

View full posting on CareerOneStop → ID: cddf848dc4ad

Staff Machine Learning Engineer

Indeed · Cheyenne, WY

Senior

2026-04-04

WY 2026-04-04

View full posting on CareerOneStop → ID: 6f508df72fca

Payer Healthcare Data Scientist, Manager

PwC · Las Vegas, NV

Manager

2026-04-04

NV 2026-04-04

View full posting on CareerOneStop → ID: b544b5355e36

Staff Machine Learning Engineer

Indeed · Las Vegas, NV

Senior

2026-04-04

NV 2026-04-04

View full posting on CareerOneStop → ID: c8d30a7ad5cb

Staff Machine Learning Engineer

Indeed · Bismarck, ND

Senior

2026-04-04

ND 2026-04-04

View full posting on CareerOneStop → ID: cb3b8b70b7f8

Staff Machine Learning Engineer

Indeed · Sioux Falls, SD

Senior

2026-04-04

SD 2026-04-04

View full posting on CareerOneStop → ID: 2f43d996a40e

Staff Machine Learning Engineer

Indeed · Albuquerque, NM

Senior

2026-04-04

NM 2026-04-04

View full posting on CareerOneStop → ID: 7772d1579731

Theoretical Biology and Biophysics Post-Bachelor Student in Data Science

Los Alamos National Laboratory · Los Alamos, NM

Mid-level

2026-04-04

NM 2026-04-04

View full posting on CareerOneStop → ID: fe44532a5af7

Staff Machine Learning Engineer

Indeed · Omaha, NE

Senior

2026-04-04

NE 2026-04-04

View full posting on CareerOneStop → ID: 538e4355470a

Staff Machine Learning Engineer

Indeed · Kansas City, KS

Senior

2026-04-04

KS 2026-04-04

View full posting on CareerOneStop → ID: 57a47994c544

Payer Healthcare Data Scientist, Manager

PwC · Oklahoma City, OK

Manager

2026-04-04

OK 2026-04-04

View full posting on CareerOneStop → ID: 8539fe57388c

Staff Machine Learning Engineer

Indeed · Oklahoma City, OK

Senior

2026-04-04

OK 2026-04-04

View full posting on CareerOneStop → ID: 1e9fb2263e37

Senior, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-04

AR 2026-04-04

View full posting on CareerOneStop → ID: 70211639d815

Staff Machine Learning Engineer

Indeed · Little Rock, AR

Senior

2026-04-04

AR 2026-04-04

View full posting on CareerOneStop → ID: 0a053f394536

Payer Healthcare Data Scientist, Manager

PwC · New Orleans, LA

Manager

2026-04-04

LA 2026-04-04

View full posting on CareerOneStop → ID: 43f34efe2062

Staff Machine Learning Engineer

Indeed · Baton Rouge, LA

Senior

2026-04-04

LA 2026-04-04

View full posting on CareerOneStop → ID: 55b81b395c54

Staff Machine Learning Engineer

Indeed · Jackson, MS

Senior

2026-04-04

MS 2026-04-04

View full posting on CareerOneStop → ID: 54da1a10acaa

Manager- Applied Sciences / Machine Learning

Microsoft Corporation · Redmond, WA

Manager Doctorate

2026-04-03

WA 2026-04-03

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience.
3+ years of people management experience.

Preferred

Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
8+ years of industry experience in software engineering and/or machine learning, with prior experience leading teams or technical leadership roles.
Solid hands-on background in machine learning, including LLMs, NLP, or recommendation systems.
Proven track record of delivering large-scale, production-grade ML systems.
Experience leading or owning critical projects in recommendation systems or AIGC scenarios.
Proficiency in programming languages such as C/C++, C#, Java, and/or Python.
Demonstrated experience managing and growing ML teams, including performance management and career development.
Solid expertise in deep learning frameworks such as TensorFlow or PyTorch.
Experience with LLM fine-tuning, evaluation, and real-world product deployment.
Experience leading projects through full product lifecycle, from concept to launch and iteration.
Background in distributed systems and large-scale data processing.
Solid foundation in data structures, algorithms, and system design.
Experience with large-scale data analytics tools such as Spark.

Responsibilities

Lead and grow a team of Applied Scientists and Machine Learning Engineers, including hiring, coaching, and developing talent across Applied Science and engineering.
Define technical vision and strategy for recommendation systems, Artificial Intelligence Generated Content (AIGC), and LLM-powered content generation.
Drive end-to-end execution across multiple initiatives, from ideation and design to production and iteration.
Oversee system architecture and scalability, ensuring robust, efficient, and high-quality ML solutions in production.
Partner cross-functionally with product, engineering, and leadership teams to align on priorities and deliver customer impact.
Champion innovation in AIGC applications, ranking, and recommendation algorithms.
Mentor and elevate the team, fostering a culture of technical excellence, collaboration, and continuous learning.
Communicate progress, insights, and strategy to senior leadership and stakeholders.

View full posting on CareerOneStop → ID: edd9ebd3d35f

AI Agent ML Engineer

Bausch + Lomb · Boise, ID

Mid-level

2026-04-03

ID 2026-04-03

View full posting on CareerOneStop → ID: fd9fd3a4eb4e

AI Agent ML Engineer

Bausch + Lomb · Cheyenne, WY

Mid-level

2026-04-03

WY 2026-04-03

View full posting on CareerOneStop → ID: 39138df87c49

AI Agent ML Engineer

Bausch + Lomb · Lincoln, NE

Mid-level

2026-04-03

NE 2026-04-03

View full posting on CareerOneStop → ID: a5e11d1bd2e3

AI Agent ML Engineer

Bausch + Lomb · Topeka, KS

Mid-level

2026-04-03

KS 2026-04-03

View full posting on CareerOneStop → ID: e1b3589e6dbc

AI Agent ML Engineer

Bausch + Lomb · Oklahoma City, OK

Mid-level

2026-04-03

OK 2026-04-03

View full posting on CareerOneStop → ID: 1f53ee4cb3b7

(USA) Staff, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-03

AR 2026-04-03

View full posting on CareerOneStop → ID: 7a534faccc09

AI Agent ML Engineer

Bausch + Lomb · Little Rock, AR

Mid-level

2026-04-03

AR 2026-04-03

View full posting on CareerOneStop → ID: 98b7888fb55b

AI Agent ML Engineer

Bausch + Lomb · Baton Rouge, LA

Mid-level

2026-04-03

LA 2026-04-03

View full posting on CareerOneStop → ID: b8525f1f67ce

AI Agent ML Engineer

Bausch + Lomb · Jackson, MS

Mid-level

2026-04-03

MS 2026-04-03

View full posting on CareerOneStop → ID: 238764fb1150

Senior Data Scientist, ORBIT

Amazon · Bellevue, WA

Senior

2026-04-02

WA 2026-04-02

View full posting on CareerOneStop → ID: 0e7af46f91f7

Staff, Data Scientist - Conversational AI

Walmart · Bellevue, WA

Senior

2026-04-02

WA 2026-04-02

View full posting on CareerOneStop → ID: 7af0c6f187d1

Staff, Data Scientist - Conversational AI

Walmart · Bellevue, WA

Senior

2026-04-02

WA 2026-04-02

View full posting on CareerOneStop → ID: cee74b686bec

Actuarial and Data Science Model Validation

The Hartford · Olympia, WA

Mid-level

2026-04-01

WA 2026-04-01

View full posting on CareerOneStop → ID: 8278027d43dd

Principal Data Scientist

Microsoft Corporation · Redmond, WA

Senior

2026-04-01

WA 2026-04-01

View full posting on CareerOneStop → ID: 26466c4c6b3d

AI & GenAI Data Scientist - EUR- Director

PwC · Portland, OR

Director

2026-04-01

WA 2026-04-01

View full posting on CareerOneStop → ID: 01299590eb13

Actuarial and Data Science Model Validation

The Hartford · Boise, ID

Mid-level

2026-04-01

ID 2026-04-01

View full posting on CareerOneStop → ID: 62c8781ca8ec

Senior Data Scientist

Micron Technology, Inc. · Boise, ID

Senior

2026-04-01

ID 2026-04-01

View full posting on CareerOneStop → ID: 5ba8159c2d13

Actuarial and Data Science Model Validation

The Hartford · Salem, OR

Mid-level

2026-04-01

OR 2026-04-01

View full posting on CareerOneStop → ID: f74ef62aaa4b

Actuarial and Data Science Model Validation

The Hartford · Helena, MT

Mid-level

2026-04-01

MT 2026-04-01

View full posting on CareerOneStop → ID: 28da9722469c

Actuarial and Data Science Model Validation

The Hartford · Cheyenne, WY

Mid-level

2026-04-01

WY 2026-04-01

View full posting on CareerOneStop → ID: 8e28441d7e2a

Actuarial and Data Science Model Validation

The Hartford · Carson City, NV

Mid-level

2026-04-01

NV 2026-04-01

View full posting on CareerOneStop → ID: 20c1e859e03c

AI & GenAI Data Scientist - EUR- Director

PwC · Las Vegas, NV

Director

2026-04-01

NV 2026-04-01

View full posting on CareerOneStop → ID: 6f39f7b7837a

Actuarial and Data Science Model Validation

The Hartford · Bismarck, ND

Mid-level

2026-04-01

ND 2026-04-01

View full posting on CareerOneStop → ID: b780a9c33bf5

Actuarial and Data Science Model Validation

The Hartford · Pierre, SD

Mid-level

2026-04-01

SD 2026-04-01

View full posting on CareerOneStop → ID: 1cf65c865591

Actuarial and Data Science Model Validation

The Hartford · Santa Fe, NM

Mid-level

2026-04-01

NM 2026-04-01

View full posting on CareerOneStop → ID: 5bce41bc8a89

Actuarial and Data Science Model Validation

The Hartford · Lincoln, NE

Mid-level

2026-04-01

NE 2026-04-01

View full posting on CareerOneStop → ID: 8e9f5bbef672

Actuarial and Data Science Model Validation

The Hartford · Oklahoma City, OK

Mid-level

2026-04-01

OK 2026-04-01

View full posting on CareerOneStop → ID: d2010924f6e7

AI & GenAI Data Scientist - EUR- Director

PwC · Tulsa, OK

Director

2026-04-01

OK 2026-04-01

View full posting on CareerOneStop → ID: 2a8c1beb2e78

AI & GenAI Data Scientist - EUR- Director

PwC · Oklahoma City, OK

Director

2026-04-01

OK 2026-04-01

View full posting on CareerOneStop → ID: e82f6c5c0a0c

(USA) Senior, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-01

AR 2026-04-01

View full posting on CareerOneStop → ID: cb17a8816eea

Actuarial and Data Science Model Validation

The Hartford · Little Rock, AR

Mid-level

2026-04-01

AR 2026-04-01

View full posting on CareerOneStop → ID: 1718464afa1e

AI & GenAI Data Scientist - EUR- Director

PwC · Fayetteville, AR

Director

2026-04-01

AR 2026-04-01

View full posting on CareerOneStop → ID: a3a1c01dda02

AI & GenAI Data Scientist - EUR- Director

PwC · Little Rock, AR

Director

2026-04-01

AR 2026-04-01

View full posting on CareerOneStop → ID: 7936e8e040ac

Actuarial and Data Science Model Validation

The Hartford · Baton Rouge, LA

Mid-level

2026-04-01

LA 2026-04-01

View full posting on CareerOneStop → ID: f4b0463cf9a5

AI & GenAI Data Scientist - EUR- Director

PwC · New Orleans, LA

Director

2026-04-01

LA 2026-04-01

View full posting on CareerOneStop → ID: b09dd0aa2e46

Actuarial and Data Science Model Validation

The Hartford · Jackson, MS

Mid-level

2026-04-01

MS 2026-04-01

View full posting on CareerOneStop → ID: 7f3be2beaeaa

Staff Machine Learning Engineer, AI Researcher

Cribl, Inc · Olympia, WA

Senior

2026-03-31

WA 2026-03-31

View full posting on CareerOneStop → ID: 3a4d61158ead

(USA) Senior Manager, Data Science - CVP Strategy & Modeling

Walmart · Bentonville, AR

Manager

2026-03-31

AR 2026-03-31

View full posting on CareerOneStop → ID: 1b213dd478e5

(USA) Senior Manager, Data Science - Mobius Digital Twin, Delivery Speed Optimization

Walmart · Bentonville, AR

Manager

2026-03-31

AR 2026-03-31

View full posting on CareerOneStop → ID: 1db2d0696687

(USA) Senior Manager, Data Science - Mobius Digital Twin, Fulfillment Network Optimization

Walmart · Bentonville, AR

Manager

2026-03-31

AR 2026-03-31

View full posting on CareerOneStop → ID: 5397af5f42f5

(USA) Senior Manager, Data Science - Strategic Execution

Walmart · Bentonville, AR

Manager

2026-03-31

AR 2026-03-31

View full posting on CareerOneStop → ID: eaeb9a8cc924

Senior Director, Data Science - CVP Strategy & Enablement

Walmart · Bentonville, AR

Director

2026-03-31

AR 2026-03-31

View full posting on CareerOneStop → ID: 62f7a98e8763

Staff Machine Learning Engineer, AI Researcher

Cribl, Inc · Clarksdale, MS

Senior

2026-03-31

MS 2026-03-31

View full posting on CareerOneStop → ID: b9a0df3fba7e

Sr Data Scientist

The Hertz Corporation · Olympia, WA

Senior

2026-03-28

WA 2026-03-28

View full posting on CareerOneStop → ID: f6b7ee993924

Sr Data Scientist

The Hertz Corporation · Boise, ID

Senior

2026-03-28

ID 2026-03-28

View full posting on CareerOneStop → ID: d1ae159e685c

Sr Data Scientist

The Hertz Corporation · Salem, OR

Senior

2026-03-28

OR 2026-03-28

View full posting on CareerOneStop → ID: 0d7ed551642a

Sr Data Scientist

The Hertz Corporation · Helena, MT

Senior

2026-03-28

MT 2026-03-28

View full posting on CareerOneStop → ID: cdd8215bf12c

Sr Data Scientist

The Hertz Corporation · Cheyenne, WY

Senior

2026-03-28

WY 2026-03-28

View full posting on CareerOneStop → ID: 5cf4314ab29d

Sr Data Scientist

The Hertz Corporation · Carson City, NV

Senior

2026-03-28

NV 2026-03-28

View full posting on CareerOneStop → ID: 274fc96d88b4

Sr Data Scientist

The Hertz Corporation · Bismarck, ND

Senior

2026-03-28

ND 2026-03-28

View full posting on CareerOneStop → ID: 6fadb33a2c41

Sr Data Scientist

The Hertz Corporation · Pierre, SD

Senior

2026-03-28

SD 2026-03-28

View full posting on CareerOneStop → ID: 61cc3c6b71fd

Sr Data Scientist

The Hertz Corporation · Santa Fe, NM

Senior

2026-03-28

NM 2026-03-28

View full posting on CareerOneStop → ID: 0a5a1acd4328

Sr Data Scientist

The Hertz Corporation · Lincoln, NE

Senior

2026-03-28

NE 2026-03-28

View full posting on CareerOneStop → ID: ded06bcafb73

Sr Data Scientist

The Hertz Corporation · Oklahoma City, OK

Senior

2026-03-28

OK 2026-03-28

View full posting on CareerOneStop → ID: e5b78e07ee7d

(USA) Senior, Data Scientist

Walmart · Bentonville, AR

Senior

2026-03-28

AR 2026-03-28

View full posting on CareerOneStop → ID: 33f34662345b

Senior, Data Scientist - Performance Measurement & Insights

Walmart · Bentonville, AR

Senior

2026-03-28

AR 2026-03-28

View full posting on CareerOneStop → ID: 8c3d717cf8e3

Sr Data Scientist

The Hertz Corporation · Little Rock, AR

Senior

2026-03-28

AR 2026-03-28

View full posting on CareerOneStop → ID: 692b6d9ecd0d

Sr Data Scientist

The Hertz Corporation · Baton Rouge, LA

Senior

2026-03-28

LA 2026-03-28

View full posting on CareerOneStop → ID: 80c8cf89f10f

Sr Data Scientist

The Hertz Corporation · Jackson, MS

Senior

2026-03-28

MS 2026-03-28

View full posting on CareerOneStop → ID: 7986eab4f56e

Data Scientist

BECU · Tukwila, WA

Mid-level

2026-03-27

WA 2026-03-27

View full posting on CareerOneStop → ID: 6dde6fb8be71

Sr Data Scientist

BECU · Tukwila, WA

Senior

2026-03-27

WA 2026-03-27

View full posting on CareerOneStop → ID: 80ccd58c001a

Senior Data Scientist

Montana State University · Bozeman, MT

Senior

2026-03-27

MT 2026-03-27

View full posting on CareerOneStop → ID: 72ccbe9d7d83

(USA) Staff, Data Scientist

Walmart · Bentonville, AR

Senior

2026-03-26

AR 2026-03-26

View full posting on CareerOneStop → ID: 61358034eb59

Sr Data / ML Engineers (PySpark / Databricks / Healthcare Claims)

Cognizant · Olympia, WA

Senior

2026-03-25

WA 2026-03-25

View full posting on CareerOneStop → ID: 64ab6a41b751

Sr Data / ML Engineers (PySpark / Databricks / Healthcare Claims)

Cognizant · Boise, ID

Senior

2026-03-25

ID 2026-03-25

View full posting on CareerOneStop → ID: 754dfcfbbf86

Sr Data / ML Engineers (PySpark / Databricks / Healthcare Claims)

Cognizant · Salem, OR

Senior

2026-03-25

OR 2026-03-25

View full posting on CareerOneStop → ID: f7d22a906e7a

Sr Data / ML Engineers (PySpark / Databricks / Healthcare Claims)

Cognizant · Helena, MT

Senior

2026-03-25

MT 2026-03-25

View full posting on CareerOneStop → ID: da1535a235cf

Sr Data / ML Engineers (PySpark / Databricks / Healthcare Claims)

Cognizant · Cheyenne, WY

Senior

2026-03-25

WY 2026-03-25

View full posting on CareerOneStop → ID: 2af789be75fe

Sr Data / ML Engineers (PySpark / Databricks / Healthcare Claims)

Cognizant · Carson City, NV

Senior

2026-03-25

NV 2026-03-25

View full posting on CareerOneStop → ID: 521160ddcfa7

Sr Data / ML Engineers (PySpark / Databricks / Healthcare Claims)

Cognizant · Bismarck, ND

Senior

2026-03-25

ND 2026-03-25

View full posting on CareerOneStop → ID: b51b85266235

Sr Data / ML Engineers (PySpark / Databricks / Healthcare Claims)

Cognizant · Pierre, SD

Senior

2026-03-25

SD 2026-03-25

View full posting on CareerOneStop → ID: 2f9952578219

Sr Data / ML Engineers (PySpark / Databricks / Healthcare Claims)

Cognizant · Santa Fe, NM

Senior

2026-03-25

NM 2026-03-25

View full posting on CareerOneStop → ID: f823c51aa4da

Sr Data / ML Engineers (PySpark / Databricks / Healthcare Claims)

Cognizant · Lincoln, NE

Senior

2026-03-25

NE 2026-03-25

View full posting on CareerOneStop → ID: 29600fcbfbf0

Sr Data / ML Engineers (PySpark / Databricks / Healthcare Claims)

Cognizant · Oklahoma City, OK

Senior

2026-03-25

OK 2026-03-25

View full posting on CareerOneStop → ID: 26a3475b25aa

(USA) Senior, Data Scientist

Walmart · Bentonville, AR

Senior

2026-03-25

AR 2026-03-25

View full posting on CareerOneStop → ID: 420748820a0d

Sr Data / ML Engineers (PySpark / Databricks / Healthcare Claims)

Cognizant · Little Rock, AR

Senior

2026-03-25

AR 2026-03-25

View full posting on CareerOneStop → ID: a75c4cf3f2c7

Data Scientist

T-Mobile USA, Inc · Bellevue, WA

Mid-level

2026-03-24

WA 2026-03-24

View full posting on CareerOneStop → ID: 66e30c7505de

Data Scientist III

Simplot · Boise, ID

Mid-level

2026-03-24

ID 2026-03-24

View full posting on CareerOneStop → ID: 109a952b4467

Principal Data Scientist

Microsoft Corporation · Redmond, WA

Senior

2026-03-21

WA 2026-03-21

View full posting on CareerOneStop → ID: 895d63e6ff0c

Staff Data Scientist

OKTA · Bellevue, WA

Senior

2026-03-21

WA 2026-03-21

View full posting on CareerOneStop → ID: 813e63619983

Principal Data Scientist

Microsoft Corporation · Redmond, WA

Senior

2026-03-20

WA 2026-03-20

View full posting on CareerOneStop → ID: 19c07196b2b9

Principal Data Scientist

Microsoft Corporation · Redmond, WA

Senior

2026-03-20

WA 2026-03-20

View full posting on CareerOneStop → ID: dfd67dc76f93

Senior Data Scientist

Microsoft Corporation · Redmond, WA

Senior

2026-03-20

WA 2026-03-20

View full posting on CareerOneStop → ID: b79c00837bd0

Sr Data Scientist

T-Mobile USA, Inc · Bellevue, WA

Senior

2026-03-20

WA 2026-03-20

View full posting on CareerOneStop → ID: 1d4484fa62a9

Staff Machine Learning Engineer, Ads Late Funnel

Pinterest, Inc. · Seattle, WA

Senior

2026-03-20

WA 2026-03-20

View full posting on CareerOneStop → ID: 9b0472a16ed2

Senior Machine Learning Engineer - Generative AI & Full-Stack Applications

CVS Health · Olympia, WA

Senior

2026-03-20

WA 2026-03-20

View full posting on CareerOneStop → ID: c99e530abc1a

Senior Machine Learning Engineer - Generative AI & Full-Stack Applications

CVS Health · Boise, ID

Senior

2026-03-20

ID 2026-03-20

View full posting on CareerOneStop → ID: 1d0b1d3c1ba3

Senior Machine Learning Engineer - Generative AI & Full-Stack Applications

CVS Health · Salem, OR

Senior

2026-03-20

OR 2026-03-20

View full posting on CareerOneStop → ID: a291e5c12d35

Senior Machine Learning Engineer - Generative AI & Full-Stack Applications

CVS Health · Helena, MT

Senior

2026-03-20

MT 2026-03-20

View full posting on CareerOneStop → ID: 7c54f1b6f348

Senior Machine Learning Engineer - Generative AI & Full-Stack Applications

CVS Health · Cheyenne, WY

Senior

2026-03-20

WY 2026-03-20

View full posting on CareerOneStop → ID: e8362000db81

Senior Machine Learning Engineer - Generative AI & Full-Stack Applications

CVS Health · Carson City, NV

Senior

2026-03-20

NV 2026-03-20

View full posting on CareerOneStop → ID: a3946df20daa

Senior Machine Learning Engineer - Generative AI & Full-Stack Applications

CVS Health · Bismarck, ND

Senior

2026-03-20

ND 2026-03-20

View full posting on CareerOneStop → ID: f0ba12e94829

Senior Machine Learning Engineer - Generative AI & Full-Stack Applications

CVS Health · Pierre, SD

Senior

2026-03-20

SD 2026-03-20

View full posting on CareerOneStop → ID: cb71fa6c4309

Senior Machine Learning Engineer - Generative AI & Full-Stack Applications

CVS Health · Santa Fe, NM

Senior

2026-03-20

NM 2026-03-20

View full posting on CareerOneStop → ID: 723958aaedce

Senior Machine Learning Engineer - Generative AI & Full-Stack Applications

CVS Health · Lincoln, NE

Senior

2026-03-20

NE 2026-03-20

View full posting on CareerOneStop → ID: 26f83816b268

Senior Machine Learning Engineer - Generative AI & Full-Stack Applications

CVS Health · Oklahoma City, OK

Senior

2026-03-20

OK 2026-03-20

View full posting on CareerOneStop → ID: 94dfdb9324ac

Senior Machine Learning Engineer - Generative AI & Full-Stack Applications

CVS Health · Little Rock, AR

Senior

2026-03-20

AR 2026-03-20

View full posting on CareerOneStop → ID: 0343e25021a7

Principal, Data Science & Analytics

Microsoft Corporation · Redmond, WA

Senior

2026-03-19

WA 2026-03-19

View full posting on CareerOneStop → ID: 25ce8075c6f4

Staff, Data Scientist

Walmart · Bentonville, AR

Senior

2026-03-19

AR 2026-03-19

View full posting on CareerOneStop → ID: 3b0fa971d08b

Data Scientist, Demand Forecasting

Amazon · Bellevue, WA

Mid-level

2026-03-18

WA 2026-03-18

View full posting on CareerOneStop → ID: 267794908dcf

Data Scientist

SOS International LLC · Salem, OR

Mid-level

2026-03-18

OR 2026-03-18

View full posting on CareerOneStop → ID: fc33e9cfa2dc

Senior Data Scientist

SOS International LLC · Salem, OR

Senior

2026-03-18

OR 2026-03-18

View full posting on CareerOneStop → ID: 31285d7a1d61

(USA) Senior, Data Scientist - Digital Twin Systems Developer

Walmart · Bentonville, AR

Senior

2026-03-18

AR 2026-03-18

View full posting on CareerOneStop → ID: 5f2b78b10f93

Principal, Data Scientist

Walmart · Bentonville, AR

Senior

2026-03-18

AR 2026-03-18

View full posting on CareerOneStop → ID: 8efa72dac48d

Principal, Data Scientist - Digital Twin Systems Architect

Walmart · Bentonville, AR

Senior

2026-03-18

AR 2026-03-18

View full posting on CareerOneStop → ID: 65fbb847a1a5

Staff Machine Learning Engineer, AI Researcher

Cribl, Inc · Olympia, WA

Senior

2026-03-17

WA 2026-03-17

View full posting on CareerOneStop → ID: fe7fa5a8f4f9

(USA) Data Scientist III

Walmart · Bentonville, AR

Mid-level

2026-03-17

AR 2026-03-17

View full posting on CareerOneStop → ID: 0c04047ed4c5

Data Scientist, Amazon Leo Global Planning, Amazon Leo

Amazon · Bellevue, WA

Mid-level

2026-03-14

WA 2026-03-14

View full posting on CareerOneStop → ID: 9cbbceb50354

Multidisciplinary Manager, Industry Solutions Engineering (ISE) / Data Science

Microsoft Corporation · Redmond, WA

Manager

2026-03-14

WA 2026-03-14

View full posting on CareerOneStop → ID: f85851ea473e

Machine Learning Scientist - GenAI, KIT

Amazon · Bellevue, WA

Mid-level

2026-03-13

WA 2026-03-13

View full posting on CareerOneStop → ID: d0513bb1c063

Senior, Data Scientist (Pricing)

Walmart · Bentonville, AR

Senior

2026-03-13

AR 2026-03-13

View full posting on CareerOneStop → ID: 3cbcfe3fc4d2

Data Scientist, Amazon Leo Global Planning, Amazon Leo

Amazon · Bellevue, WA

Mid-level

2026-03-13

WA 2026-03-13

View full posting on CareerOneStop → ID: ac40f88c9ae9

Distinguished, Data Scientist

Walmart · Bellevue, WA

Senior

2026-03-12

WA 2026-03-12

View full posting on CareerOneStop → ID: 3ff6bdbf3185

Senior Applied Data Scientist

Microsoft Corporation · Redmond, WA

Senior

2026-03-12

WA 2026-03-12

View full posting on CareerOneStop → ID: fcb2ffa9a7de

(USA) Senior Manager, Data Science, Perishable First Mile

Walmart · Bentonville, AR

Manager

2026-03-12

AR 2026-03-12

View full posting on CareerOneStop → ID: c2e4ef72f1f1

Principal, Data Science & Analytics

Microsoft Corporation · Redmond, WA

Senior

2026-03-08

WA 2026-03-08

View full posting on CareerOneStop → ID: fa4b158098d7

Data Scientist

The Gores Group, LLC · Remote, OR

Mid-level

2026-03-08

OR 2026-03-08

View full posting on CareerOneStop → ID: 85ee686aef51

Staff Machine Learning Engineer - Mapping

General Motors · Olympia, WA

Senior

2026-03-07

WA 2026-03-07

View full posting on CareerOneStop → ID: 87d7668f5e66

Staff ML Engineer - Embodied AI Offboard Perception

General Motors · Olympia, WA

Senior

2026-03-07

WA 2026-03-07

View full posting on CareerOneStop → ID: ae3fc6db72ca

Senior Staff Data Scientist, Product

Google · Kirkland, WA

Senior

2026-03-07

WA 2026-03-07

View full posting on CareerOneStop → ID: 92f37facc8ad

Staff Data Scientist, Product

Google · Kirkland, WA

Senior

2026-03-07

WA 2026-03-07

View full posting on CareerOneStop → ID: 55a2e1c0574a

Machine Learning Engineer

Micron Technology, Inc. · Boise, ID

Mid-level

2026-03-07

ID 2026-03-07

View full posting on CareerOneStop → ID: a6a0c7355d59

Principal Data Scientist

Sedgwick · Boise, ID

Senior

2026-03-07

ID 2026-03-07

View full posting on CareerOneStop → ID: a2817953ddb7

Staff Machine Learning Engineer - Mapping

General Motors · Boise, ID

Senior

2026-03-07

ID 2026-03-07

View full posting on CareerOneStop → ID: 0392c8ecf727

Staff Machine Learning Engineer - Mapping

General Motors · Salem, OR

Senior

2026-03-07

OR 2026-03-07

View full posting on CareerOneStop → ID: 084faf3e41d6

Principal Data Scientist

Sedgwick · Missoula, MT

Senior

2026-03-07

MT 2026-03-07

View full posting on CareerOneStop → ID: 8fd93ae533a5

Principal Data Scientist

Sedgwick · Helena, MT

Senior

2026-03-07

MT 2026-03-07

View full posting on CareerOneStop → ID: 178b619ff539

Staff Machine Learning Engineer - Mapping

General Motors · Helena, MT

Senior

2026-03-07

MT 2026-03-07

View full posting on CareerOneStop → ID: 3430eee16c58

Principal Data Scientist

Sedgwick · Cheyenne, WY

Senior

2026-03-07

WY 2026-03-07

View full posting on CareerOneStop → ID: f56d7f1ffe17

Staff Machine Learning Engineer - Mapping

General Motors · Cheyenne, WY

Senior

2026-03-07

WY 2026-03-07

View full posting on CareerOneStop → ID: d84dbb9bebad

Staff Machine Learning Engineer - Mapping

General Motors · Carson City, NV

Senior

2026-03-07

NV 2026-03-07

View full posting on CareerOneStop → ID: 52ea0d44d36e

Principal Data Scientist

Sedgwick · Bismarck, ND

Senior

2026-03-07

ND 2026-03-07

View full posting on CareerOneStop → ID: 844cc5c71b0f

Principal Data Scientist

Sedgwick · Fargo, ND

Senior

2026-03-07

ND 2026-03-07

View full posting on CareerOneStop → ID: 5af4c84badee

Staff Machine Learning Engineer - Mapping

General Motors · Bismarck, ND

Senior

2026-03-07

ND 2026-03-07

View full posting on CareerOneStop → ID: cfc292aafecd

Principal Data Scientist

Sedgwick · Rapid City, SD

Senior

2026-03-07

SD 2026-03-07

View full posting on CareerOneStop → ID: 1665561feb46

Principal Data Scientist

Sedgwick · Sioux Falls, SD

Senior

2026-03-07

SD 2026-03-07

View full posting on CareerOneStop → ID: 1b21cd539991

Principal Data Scientist

Sedgwick · Pierre, SD

Senior

2026-03-07

SD 2026-03-07

View full posting on CareerOneStop → ID: 8e8da616ef3a

Staff Machine Learning Engineer - Mapping

General Motors · Pierre, SD

Senior

2026-03-07

SD 2026-03-07

View full posting on CareerOneStop → ID: 154054ed708e

Principal Data Scientist

Sedgwick · Albuquerque, NM

Senior

2026-03-07

NM 2026-03-07

View full posting on CareerOneStop → ID: 6cc7aba6e9ee

Principal Data Scientist

Sedgwick · Santa Fe, NM

Senior

2026-03-07

NM 2026-03-07

View full posting on CareerOneStop → ID: a0a9b1e82218

Staff Machine Learning Engineer - Mapping

General Motors · Santa Fe, NM

Senior

2026-03-07

NM 2026-03-07

View full posting on CareerOneStop → ID: 187341680593

Principal Data Scientist

Sedgwick · Omaha, NE

Senior

2026-03-07

NE 2026-03-07

View full posting on CareerOneStop → ID: 03a6494d60b6

Principal Data Scientist

Sedgwick · Lincoln, NE

Senior

2026-03-07

NE 2026-03-07

View full posting on CareerOneStop → ID: c8d1acd67628

Staff Machine Learning Engineer - Mapping

General Motors · Lincoln, NE

Senior

2026-03-07

NE 2026-03-07

View full posting on CareerOneStop → ID: 0631472186dc

Principal Data Scientist

Sedgwick · Little Rock, AR

Senior

2026-03-07

AR 2026-03-07

View full posting on CareerOneStop → ID: 9223655b5ee8

Staff Machine Learning Engineer - Mapping

General Motors · Little Rock, AR

Senior

2026-03-07

AR 2026-03-07

View full posting on CareerOneStop → ID: 25e58872c8b3

Data Scientist

Micron Technology, Inc. · Boise, ID

Mid-level

2026-03-06

ID 2026-03-06

View full posting on CareerOneStop → ID: 522af9f32aff

Principal ML Engineer - Embodied AI Scaling Foundations

General Motors · Olympia, WA

Senior

2026-03-05

WA 2026-03-05

View full posting on CareerOneStop → ID: 7e174aa8879f

Senior ML Engineer - Embodied AI Scaling Foundations

General Motors · Olympia, WA

Senior

2026-03-05

WA 2026-03-05

View full posting on CareerOneStop → ID: cc650b47e9be

Staff ML Engineer - Embodied AI Scaling Foundations

General Motors · Olympia, WA

Senior

2026-03-05

WA 2026-03-05

View full posting on CareerOneStop → ID: 4cabf215efb6

Data Scientist 4

Bucher & Christian Consulting, Inc. dba BCforward (BCF) · Redmond, WA

Mid-level

2026-03-05

WA 2026-03-05

View full posting on CareerOneStop → ID: cbd4751c7b60

Senior Director, Data Science

Visa Usa Inc · Bellevue, WA

Director

2026-03-05

WA 2026-03-05

View full posting on CareerOneStop → ID: 909eb7c9fb41

Principal Data Scientist

Microsoft Corporation · Redmond, WA

Senior

2026-03-04

WA 2026-03-04

View full posting on CareerOneStop → ID: 2d2633fc04f2

Machine Learning Engineering Manager, Model Delivery

Autodesk · Portland, OR

Manager

2026-03-03

WA 2026-03-03

View full posting on CareerOneStop → ID: c0a5e990de8a

Senior Technical Program Manager I, Machine Learning, Google Cloud Platforms

Google · Kirkland, WA

Manager

2026-02-28

WA 2026-02-28

View full posting on CareerOneStop → ID: 2f8cbca4a69e

Lead Data Scientist - Safety Alignment

Humana · Olympia, WA

Senior

2026-02-27

WA 2026-02-27

View full posting on CareerOneStop → ID: 1e150ea50b8e

Data Scientist, Rapid & Rural Logistics (R2L)

Amazon · Bellevue, WA

Mid-level

2026-02-27

WA 2026-02-27

View full posting on CareerOneStop → ID: a358c0d3070d

Lead Data Scientist - Safety Alignment

Humana · Boise, ID

Senior

2026-02-27

ID 2026-02-27

View full posting on CareerOneStop → ID: 8ab5926fb48b

Lead Data Scientist - Safety Alignment

Humana · Salem, OR

Senior

2026-02-27

OR 2026-02-27

View full posting on CareerOneStop → ID: 3b4260d76e5d

Lead Data Scientist - Safety Alignment

Humana · Helena, MT

Senior

2026-02-27

MT 2026-02-27

View full posting on CareerOneStop → ID: 006320b2a286

Lead Data Scientist - Safety Alignment

Humana · Cheyenne, WY

Senior

2026-02-27

WY 2026-02-27

View full posting on CareerOneStop → ID: d5463e948e92

Lead Data Scientist - Safety Alignment

Humana · Bismarck, ND

Senior

2026-02-27

ND 2026-02-27

View full posting on CareerOneStop → ID: b7ddc4f67cbd

Lead Data Scientist - Safety Alignment

Humana · Pierre, SD

Senior

2026-02-27

SD 2026-02-27

View full posting on CareerOneStop → ID: be51fab1d823

Lead Data Scientist - Safety Alignment

Humana · Santa Fe, NM

Senior

2026-02-27

NM 2026-02-27

View full posting on CareerOneStop → ID: 9032f55d1d5a

Lead Data Scientist - Safety Alignment

Humana · Lincoln, NE

Senior

2026-02-27

NE 2026-02-27

View full posting on CareerOneStop → ID: 50a3a90b5eba

Senior Data Scientist, Amazon Stores Finance Science, Amazon Stores Finance Science

Amazon · Bellevue, WA

Senior

2026-02-25

WA 2026-02-25

View full posting on CareerOneStop → ID: 59cc71fa6c33

Sr Engineer, Machine Learning Engineering

T-Mobile USA, Inc · Bellevue, WA

Senior

2026-02-23

WA 2026-02-23

View full posting on CareerOneStop → ID: 0d06045edb06

Senior Data Scientist

Microsoft Corporation · Redmond, WA

Senior

2026-02-20

WA 2026-02-20

View full posting on CareerOneStop → ID: 4d0fba48693a

Principal Data Scientist

Visa Usa Inc · Bellevue, WA

Senior

2026-02-15

WA 2026-02-15

View full posting on CareerOneStop → ID: 4e2747301a2b

Robotics - Data Science Intern / Co-op - 2026

Amazon · Bellevue, WA

Intern

2026-02-15

WA 2026-02-15

View full posting on CareerOneStop → ID: 3dec79c5a4ca

Data Scientist

Capgemini · Bellevue, WA

Mid-level

2026-02-14

WA 2026-02-14

View full posting on CareerOneStop → ID: 58e118dde5e8

Senior Machine Learning Platform Engineer (Platform)

Coinbase · Olympia, WA

Senior

2026-02-13

WA 2026-02-13

View full posting on CareerOneStop → ID: ff7dd28d8ff6

Senior Machine Learning Platform Engineer (Platform)

Coinbase · Boise, ID

Senior

2026-02-13

ID 2026-02-13

View full posting on CareerOneStop → ID: 7a6ec5694ca0

Senior Machine Learning Platform Engineer (Platform)

Coinbase · Salem, OR

Senior

2026-02-13

OR 2026-02-13

View full posting on CareerOneStop → ID: 5a824cbe9a35

Senior Machine Learning Platform Engineer (Platform)

Coinbase · Helena, MT

Senior

2026-02-13

MT 2026-02-13

View full posting on CareerOneStop → ID: 4fe8e1422198

Senior Machine Learning Platform Engineer (Platform)

Coinbase · Cheyenne, WY

Senior

2026-02-13

WY 2026-02-13

View full posting on CareerOneStop → ID: ca0c6f79739a

Senior Machine Learning Platform Engineer (Platform)

Coinbase · Bismarck, ND

Senior

2026-02-13

ND 2026-02-13

View full posting on CareerOneStop → ID: 9e6918a4810d

Senior Machine Learning Platform Engineer (Platform)

Coinbase · Pierre, SD

Senior

2026-02-13

SD 2026-02-13

View full posting on CareerOneStop → ID: 94029a487e78

Senior Machine Learning Platform Engineer (Platform)

Coinbase · Santa Fe, NM

Senior

2026-02-13

NM 2026-02-13

View full posting on CareerOneStop → ID: 2e833fe6f818

Senior Machine Learning Platform Engineer (Platform)

Coinbase · Lincoln, NE

Senior

2026-02-13

NE 2026-02-13

View full posting on CareerOneStop → ID: dbf91a827df4

Senior Machine Learning Engineer

General Motors · Boise, ID

Senior

2026-02-12

ID 2026-02-12

View full posting on CareerOneStop → ID: 9fb0a450d336

Senior Machine Learning Engineer

General Motors · Salem, OR

Senior

2026-02-12

OR 2026-02-12

View full posting on CareerOneStop → ID: 2271c961e7af

Senior Machine Learning Engineer

General Motors · Helena, MT

Senior

2026-02-12

MT 2026-02-12

View full posting on CareerOneStop → ID: 678d65312ffc

Senior Machine Learning Engineer

General Motors · Cheyenne, WY

Senior

2026-02-12

WY 2026-02-12

View full posting on CareerOneStop → ID: baffb506a61e

Senior Machine Learning Engineer

General Motors · Bismarck, ND

Senior

2026-02-12

ND 2026-02-12

View full posting on CareerOneStop → ID: d8fda15f3d16

Senior Machine Learning Engineer

General Motors · Pierre, SD

Senior

2026-02-12

SD 2026-02-12

View full posting on CareerOneStop → ID: 964043afea68

Senior Machine Learning Engineer

General Motors · Santa Fe, NM

Senior

2026-02-12

NM 2026-02-12

View full posting on CareerOneStop → ID: 0348a38a679b

Senior Machine Learning Engineer

General Motors · Lincoln, NE

Senior

2026-02-12

NE 2026-02-12

View full posting on CareerOneStop → ID: 731beb00d55e

Principal Data Scientist

Microsoft Corporation · Redmond, WA

Senior

2026-02-11

WA 2026-02-11

View full posting on CareerOneStop → ID: fbb428748046

Senior Software Engineer, Machine Learning, Google Cloud Compute

Google · Kirkland, WA

Senior

2026-02-10

WA 2026-02-10

View full posting on CareerOneStop → ID: 347e421a8d89

Senior Researcher - Machine Learning - Microsoft Research

Microsoft Corporation · Redmond, WA

Senior

2026-02-08

WA 2026-02-08

View full posting on CareerOneStop → ID: 5b361e3b1e35

Senior Researcher - Machine Learning for Life Sciences - Microsoft Research

Microsoft Corporation · Redmond, WA

Senior

2026-02-08

WA 2026-02-08

View full posting on CareerOneStop → ID: d33ca032ca5d

Senior Data Scientist

Microsoft Corporation · Redmond, WA

Senior

2026-02-08

WA 2026-02-08

View full posting on CareerOneStop → ID: f0709c3d86ad

AI & Machine Learning Engineering Consultant - Life Sciences Sector - Manager - Consulting

EY · Olympia, WA

Manager

2026-02-06

WA 2026-02-06

View full posting on CareerOneStop → ID: a87f2bc5ca62

AI & Machine Learning Engineering Consultant - Life Sciences Sector - Senior - Consulting

EY · Olympia, WA

Senior

2026-02-06

WA 2026-02-06

View full posting on CareerOneStop → ID: e036cf1793f4

AI & Machine Learning Engineering Consultant - Life Sciences Sector - Manager - Consulting

EY · Portland, OR

Manager

2026-02-06

WA 2026-02-06

View full posting on CareerOneStop → ID: 7a6e8b802069

AI & Machine Learning Engineering Consultant - Life Sciences Sector - Senior - Consulting

EY · Portland, OR

Senior

2026-02-06

WA 2026-02-06

View full posting on CareerOneStop → ID: bf38d1d8b741

AI & Machine Learning Engineering Consultant - Life Sciences Sector - Manager - Consulting

EY · Salem, OR

Manager

2026-02-06

OR 2026-02-06

View full posting on CareerOneStop → ID: 1c4c68f5ff1a

AI & Machine Learning Engineering Consultant - Life Sciences Sector - Senior - Consulting

EY · Salem, OR

Senior

2026-02-06

OR 2026-02-06

View full posting on CareerOneStop → ID: 6465eee93de9

Post-Baccalaureate Student in Computer Science and Data Science for Materials Characterization

Los Alamos National Laboratory · Los Alamos, NM

Mid-level

2026-02-04

NM 2026-02-04

View full posting on CareerOneStop → ID: 98e421945659

Data Scientist, LM Simulations Engineering, AMZL Simulations & Analytics Engineering

Amazon · Bellevue, WA

Mid-level

2026-02-01

WA 2026-02-01

View full posting on CareerOneStop → ID: 5f389c4f72f9

Senior Data Scientist, Pricing, Amazon Shipping, Amazon Shipping

Amazon · Bellevue, WA

Senior

2026-01-31

WA 2026-01-31

View full posting on CareerOneStop → ID: 15ea24045e31

People Tech - System Architect-Data Science Senior Manager

PwC · Portland, OR

Manager

2026-01-30

WA 2026-01-30

View full posting on CareerOneStop → ID: cf8492883f62

Senior Data Scientist - Microsoft Advertising

Microsoft Corporation · Redmond, WA

Senior

2026-01-29

WA 2026-01-29

View full posting on CareerOneStop → ID: bc33e5cde6e3

Sr Data Scientist, TPG

Micron Technology, Inc. · Boise, ID

Senior

2026-01-29

ID 2026-01-29

View full posting on CareerOneStop → ID: 91a7dab7ad45

Senior Data Scientist, Amazon Global Logistics

Amazon · Bellevue, WA

Senior

2026-01-28

WA 2026-01-28

View full posting on CareerOneStop → ID: e199d97312a6

Data-driven and Machine Learning Postdoctoral Research Associate

Los Alamos National Laboratory · Los Alamos, NM

Entry-level

2026-01-28

NM 2026-01-28

View full posting on CareerOneStop → ID: a7853d6c51a3

AI Agent ML Engineer

Bausch + Lomb · Olympia, WA

Mid-level

2026-01-27

WA 2026-01-27

View full posting on CareerOneStop → ID: a90f86807435

AI Agent ML Engineer

Bausch + Lomb · Salem, OR

Mid-level

2026-01-27

OR 2026-01-27

View full posting on CareerOneStop → ID: 0c4cfad75528

AI Agent ML Engineer

Bausch + Lomb · Helena, MT

Mid-level

2026-01-27

MT 2026-01-27

View full posting on CareerOneStop → ID: 7f9042d9da4e

AI Agent ML Engineer

Bausch + Lomb · Bismarck, ND

Mid-level

2026-01-27

ND 2026-01-27

View full posting on CareerOneStop → ID: ea6f4617a652

AI Agent ML Engineer

Bausch + Lomb · Pierre, SD

Mid-level

2026-01-27

SD 2026-01-27

View full posting on CareerOneStop → ID: 0f562f50fe4c

AI Agent ML Engineer

Bausch + Lomb · Santa Fe, NM

Mid-level

2026-01-27

NM 2026-01-27

View full posting on CareerOneStop → ID: 74e15064f028

Senior Machine Learning Engineer

General Motors · Olympia, WA

Senior

2026-01-23

WA 2026-01-23

View full posting on CareerOneStop → ID: f8c3e4b82907

Data Scientist

Insight Global · Portland, OR

Mid-level

2026-01-23

WA 2026-01-23

View full posting on CareerOneStop → ID: 55331c8f9841

Data Scientist

Leidos · Omaha, NE

Mid-level

2026-01-10

NE 2026-01-10

View full posting on CareerOneStop → ID: 49511e1bd1ae

Robotics - Applied Scientist II Intern / Co-op - 2026 (Robotics, Manipulation, Perception, Motion Planning, Autonomous Mobile Robots, Computer Vision, Machine Learning, Controls, and more)

Amazon · Bellevue, WA

Intern

2026-01-09

WA 2026-01-09

View full posting on CareerOneStop → ID: 577fd27f3331

Data Scientist I

Battelle Memorial Institute · Cannon AFB, NM

Entry-level

2025-12-30

NM 2025-12-30

View full posting on CareerOneStop → ID: 0666cded6135

Data Scientist II

Microsoft Corporation · Redmond, WA

Mid-level

2025-12-21

WA 2025-12-21

View full posting on CareerOneStop → ID: 5b4e6e51a63b

Principal Data Scientist - CoreAI

Microsoft Corporation · Redmond, WA

Senior

2025-12-20

WA 2025-12-20

View full posting on CareerOneStop → ID: e4ae8aa6edc6

Machine Learning Scientist II

Microsoft Corporation · Redmond, WA

Mid-level

2025-12-20

WA 2025-12-20

View full posting on CareerOneStop → ID: 4b1f65d85ecc

Principal Machine Learning Engineer

Microsoft Corporation · Redmond, WA

Senior

2025-12-19

WA 2025-12-19

View full posting on CareerOneStop → ID: 4c2416b5d5e5

Human Performance Data Scientist II

General Dynamics Information Technology · Mcchord Afb, WA

Mid-level

2025-12-04

WA 2025-12-04

View full posting on CareerOneStop → ID: 1bf5c4ea4c34

Human Performance Data Scientist I

General Dynamics Information Technology · Mcchord Afb, WA

Entry-level

2025-12-03

WA 2025-12-03

View full posting on CareerOneStop → ID: 960ffd4a45dd

Research Intern - Machine Learning and Optimization - Redmond

Microsoft Corporation · Redmond, WA

Intern

2025-11-22

WA 2025-11-22

View full posting on CareerOneStop → ID: 7240418ad404

Principal Data Scientist

Microsoft Corporation · Redmond, WA

Senior

2025-11-20

WA 2025-11-20

View full posting on CareerOneStop → ID: afd48e2b845e

AI & Machine Learning Engineering Consultant - Manager - Consulting - Location OPEN

EY · Olympia, WA

Manager

2025-11-18

WA 2025-11-18

View full posting on CareerOneStop → ID: a2ec8ad7155f

AI & Machine Learning Engineering Consultant - Senior - Consulting - Location OPEN

EY · Olympia, WA

Senior

2025-11-18

WA 2025-11-18

View full posting on CareerOneStop → ID: a2ad57ba1203

AI & Machine Learning Engineering Consultant - Manager - Consulting - Location OPEN

EY · Portland, OR

Manager

2025-11-18

WA 2025-11-18

View full posting on CareerOneStop → ID: 198e6be49977

AI & Machine Learning Engineering Consultant - Senior - Consulting - Location OPEN

EY · Portland, OR

Senior

2025-11-18

WA 2025-11-18

View full posting on CareerOneStop → ID: 9d09b9470955

AI & Machine Learning Engineering Consultant - Manager - Consulting - Location OPEN

EY · Salem, OR

Manager

2025-11-18

OR 2025-11-18

View full posting on CareerOneStop → ID: 36fef962403d

AI & Machine Learning Engineering Consultant - Senior - Consulting - Location OPEN

EY · Salem, OR

Senior

2025-11-18

OR 2025-11-18

View full posting on CareerOneStop → ID: da56afc1646e

Staff AI/ML Engineer - CI Platform

General Motors · Olympia, WA

Senior

2025-10-31

WA 2025-10-31

View full posting on CareerOneStop → ID: 170e0da38f3c

Data Science Manager, PXT Central Science

Amazon · Bellevue, WA

Manager

2025-10-16

WA 2025-10-16

View full posting on CareerOneStop → ID: 202028e6da83

Software Engineer, PhD, Early Career, AI/Machine Learning, 2026 Start

Google · Kirkland, WA

Entry-level

2025-10-01

WA 2025-10-01

View full posting on CareerOneStop → ID: 8e1a2b92df08

Data Science Manager, GenAI - SFL Scientific

Deloitte · Portland, OR

Manager

2025-09-24

WA 2025-09-24

View full posting on CareerOneStop → ID: bd4a274abfc9

Data Scientist, Analytics (Technical Leadership)

Meta · Olympia, WA

Senior

2025-09-18

WA 2025-09-18

View full posting on CareerOneStop → ID: 72f14fe5ca75

Data Scientist, Analytics (Technical Leadership)

Meta · Olympia, WA

Senior

2025-09-18

WA 2025-09-18

View full posting on CareerOneStop → ID: f9c3ed566db4

Data Scientist, Analytics (Technical Leadership)

Meta · Boise, ID

Senior

2025-09-18

ID 2025-09-18

View full posting on CareerOneStop → ID: 4ef4c1e74ab9

Data Scientist, Analytics (Technical Leadership)

Meta · Salem, OR

Senior

2025-09-18

OR 2025-09-18

View full posting on CareerOneStop → ID: 74a75a2a5c2b

Data Scientist, Analytics (Technical Leadership)

Meta · Salem, OR

Senior

2025-09-18

OR 2025-09-18

View full posting on CareerOneStop → ID: cc4a932e395f

Data Scientist, Analytics (Technical Leadership)

Meta · Helena, MT

Senior

2025-09-18

MT 2025-09-18

View full posting on CareerOneStop → ID: 39fac5e9d91d

Data Scientist, Analytics (Technical Leadership)

Meta · Cheyenne, WY

Senior

2025-09-18

WY 2025-09-18

View full posting on CareerOneStop → ID: ec82016409da

Data Scientist, Analytics (Technical Leadership)

Meta · Cheyenne, WY

Senior

2025-09-18

WY 2025-09-18

View full posting on CareerOneStop → ID: b59f6c802858

Data Scientist, Analytics (Technical Leadership)

Meta · Bismarck, ND

Senior

2025-09-18

ND 2025-09-18

View full posting on CareerOneStop → ID: 4087ea8dec94

Data Scientist, Analytics (Technical Leadership)

Meta · Bismarck, ND

Senior

2025-09-18

ND 2025-09-18

View full posting on CareerOneStop → ID: 95d3bf8a2253

Data Scientist, Analytics (Technical Leadership)

Meta · Pierre, SD

Senior

2025-09-18

SD 2025-09-18

View full posting on CareerOneStop → ID: 0293798b8e48

Data Scientist, Analytics (Technical Leadership)

Meta · Pierre, SD

Senior

2025-09-18

SD 2025-09-18

View full posting on CareerOneStop → ID: dd97307bc804

Software Engineer (Technical Leadership) - Machine Learning

Meta · Olympia, WA

Senior

2025-09-12

WA 2025-09-12

View full posting on CareerOneStop → ID: 766223be69a1

Software Engineer (Technical Leadership) - Machine Learning

Meta · Olympia, WA

Senior

2025-09-12

WA 2025-09-12

View full posting on CareerOneStop → ID: 6deb84704433

Software Engineer (Technical Leadership) - Machine Learning

Meta · Helena, MT

Senior

2025-09-12

MT 2025-09-12

View full posting on CareerOneStop → ID: 8342d08f7962

Software Engineer (Technical Leadership) - Machine Learning

Meta · Boise, ID

Senior

2025-09-12

ID 2025-09-12

View full posting on CareerOneStop → ID: 0eb236dbc43f

Software Engineer (Technical Leadership) - Machine Learning

Meta · Salem, OR

Senior

2025-09-12

OR 2025-09-12

View full posting on CareerOneStop → ID: 3b25416bf03a

Software Engineer (Technical Leadership) - Machine Learning

Meta · Salem, OR

Senior

2025-09-12

OR 2025-09-12

View full posting on CareerOneStop → ID: e82c9f676903

Software Engineer (Technical Leadership) - Machine Learning

Meta · Redmond, WA

Senior

2025-08-21

WA 2025-08-21

View full posting on CareerOneStop → ID: 576af6c9fd36

Lead Data Scientist - Autonomous Goal Management

Humana · Olympia, WA

Manager

2025-08-16

WA 2025-08-16

View full posting on CareerOneStop → ID: a67f9baf10f1

Lead Data Scientist - Autonomous Goal Management

Humana · Boise, ID

Manager

2025-08-16

ID 2025-08-16

View full posting on CareerOneStop → ID: 1aec76452e10

Lead Data Scientist - Autonomous Goal Management

Humana · Salem, OR

Manager

2025-08-16

OR 2025-08-16

View full posting on CareerOneStop → ID: 723904ea4996

Lead Data Scientist - Autonomous Goal Management

Humana · Helena, MT

Manager

2025-08-16

MT 2025-08-16

View full posting on CareerOneStop → ID: 3fdb37a1326d

Lead Data Scientist - Autonomous Goal Management

Humana · Cheyenne, WY

Manager

2025-08-16

WY 2025-08-16

View full posting on CareerOneStop → ID: 2845e0bf0ca0

Lead Data Scientist - Autonomous Goal Management

Humana · Bismarck, ND

Manager

2025-08-16

ND 2025-08-16

View full posting on CareerOneStop → ID: c09f95d1db36

Lead Data Scientist - Autonomous Goal Management

Humana · Pierre, SD

Manager

2025-08-16

SD 2025-08-16

View full posting on CareerOneStop → ID: 5fc6aa68f299

Data Scientist, SCOT Forecasting and Labs - CIV Team

Amazon · Bellevue, WA

Mid-level

2025-07-22

WA 2025-07-22

View full posting on CareerOneStop → ID: b4266522b631

Software Engineer, Machine Learning

Meta · Olympia, WA

Mid-level

2025-07-19

WA 2025-07-19

View full posting on CareerOneStop → ID: 9bf84b2b91c9

Software Engineer, Machine Learning

Meta · Olympia, WA

Mid-level

2025-07-19

WA 2025-07-19

View full posting on CareerOneStop → ID: 5e4b5b2806e1

Software Engineer, Machine Learning

Meta · Boise, ID

Mid-level

2025-07-19

ID 2025-07-19

View full posting on CareerOneStop → ID: ba87e9a8a6e6

Software Engineer, Machine Learning

Meta · Salem, OR

Mid-level

2025-07-19

OR 2025-07-19

View full posting on CareerOneStop → ID: 2dab5875a07e

Software Engineer, Machine Learning

Meta · Salem, OR

Mid-level

2025-07-19

OR 2025-07-19

View full posting on CareerOneStop → ID: 00c5be86b94a

Software Engineer, Machine Learning

Meta · Helena, MT

Mid-level

2025-07-19

MT 2025-07-19

View full posting on CareerOneStop → ID: 3b7ae35a6290

Software Engineer, Machine Learning

Meta · Cheyenne, WY

Mid-level

2025-07-19

WY 2025-07-19

View full posting on CareerOneStop → ID: fdc343f8d69d

Software Engineer, Machine Learning

Meta · Cheyenne, WY

Mid-level

2025-07-19

WY 2025-07-19

View full posting on CareerOneStop → ID: 762d43c9695e

Software Engineer, Machine Learning

Meta · Bismarck, ND

Mid-level

2025-07-19

ND 2025-07-19

View full posting on CareerOneStop → ID: 97356abc7b2c

Software Engineer, Machine Learning

Meta · Bismarck, ND

Mid-level

2025-07-19

ND 2025-07-19

View full posting on CareerOneStop → ID: a7827d6268b7

Software Engineer, Machine Learning

Meta · Pierre, SD

Mid-level

2025-07-19

SD 2025-07-19

View full posting on CareerOneStop → ID: b5db950c2ba6

Software Engineer, Machine Learning

Meta · Pierre, SD

Mid-level

2025-07-19

SD 2025-07-19

View full posting on CareerOneStop → ID: b2b784bcbf74

Software Engineer, Machine Learning

Meta · Redmond, WA

Mid-level

2025-07-09

WA 2025-07-09

View full posting on CareerOneStop → ID: 1712d7e86420

Software Engineer, Machine Learning

Meta · Redmond, WA

Mid-level

2025-07-09

WA 2025-07-09

View full posting on CareerOneStop → ID: ac83f545533e

Software Engineer, Machine Learning

Meta · Olympia, WA

Mid-level

2025-06-27

WA 2025-06-27

View full posting on CareerOneStop → ID: 88d4c79b19ef

Software Engineer, Machine Learning

Meta · Olympia, WA

Mid-level

2025-06-27

WA 2025-06-27

View full posting on CareerOneStop → ID: df4bbca20659

Software Engineer, Machine Learning

Meta · Bellevue, WA

Mid-level

2025-06-27

WA 2025-06-27

View full posting on CareerOneStop → ID: 4d0a38f4cabd

Software Engineer, Machine Learning

Meta · Bellevue, WA

Mid-level

2025-06-27

WA 2025-06-27

View full posting on CareerOneStop → ID: 90e22cd1e9b1

Software Engineer, Machine Learning

Meta · Boise, ID

Mid-level

2025-06-27

ID 2025-06-27

View full posting on CareerOneStop → ID: a3e6db61716f

Software Engineer, Machine Learning

Meta · Salem, OR

Mid-level

2025-06-27

OR 2025-06-27

View full posting on CareerOneStop → ID: 96bf34a0a307

Software Engineer, Machine Learning

Meta · Salem, OR

Mid-level

2025-06-27

OR 2025-06-27

View full posting on CareerOneStop → ID: ef877e3813b7

Software Engineer, Machine Learning

Meta · Helena, MT

Mid-level

2025-06-27

MT 2025-06-27

View full posting on CareerOneStop → ID: 41621a2eb0a4

Software Engineer, Machine Learning

Meta · Cheyenne, WY

Mid-level

2025-06-27

WY 2025-06-27

View full posting on CareerOneStop → ID: 4de8da760254

Software Engineer, Machine Learning

Meta · Cheyenne, WY

Mid-level

2025-06-27

WY 2025-06-27

View full posting on CareerOneStop → ID: 7fd745ee67f4

Software Engineer, Machine Learning

Meta · Bismarck, ND

Mid-level

2025-06-27

ND 2025-06-27

View full posting on CareerOneStop → ID: 866ca3a68b6f

Software Engineer, Machine Learning

Meta · Bismarck, ND

Mid-level

2025-06-27

ND 2025-06-27

View full posting on CareerOneStop → ID: ed9698c2c87d

Software Engineer, Machine Learning

Meta · Pierre, SD

Mid-level

2025-06-27

SD 2025-06-27

View full posting on CareerOneStop → ID: af2569a752c7

Software Engineer, Machine Learning

Meta · Pierre, SD

Mid-level

2025-06-27

SD 2025-06-27

View full posting on CareerOneStop → ID: 4fb34366646d

Data Scientist, Analytics (Technical Leadership)

Meta · Bellevue, WA

Senior

2025-06-25

WA 2025-06-25

View full posting on CareerOneStop → ID: 57c81b252a32

Software Engineer (Technical Leadership) - Machine Learning

Meta · Bellevue, WA

Senior

2025-06-25

WA 2025-06-25

View full posting on CareerOneStop → ID: 92526bce4f3f

Software Engineer, Machine Learning

Meta · Bellevue, WA

Mid-level

2025-06-25

WA 2025-06-25

View full posting on CareerOneStop → ID: 3d4de48a9c8f

Staff Software Engineer - Machine Learning

General Motors · Olympia, WA

Senior

2025-05-25

WA 2025-05-25

View full posting on CareerOneStop → ID: 28965d8a3f2d

Staff Software Engineer - Machine Learning

General Motors · Boise, ID

Senior

2025-05-25

ID 2025-05-25

View full posting on CareerOneStop → ID: 1e88f70a5937

Staff Software Engineer - Machine Learning

General Motors · Salem, OR

Senior

2025-05-25

OR 2025-05-25

View full posting on CareerOneStop → ID: f9dc15231e59

Staff Software Engineer - Machine Learning

General Motors · Helena, MT

Senior

2025-05-25

MT 2025-05-25

View full posting on CareerOneStop → ID: f5b0a9b89b9f

Staff Software Engineer - Machine Learning

General Motors · Cheyenne, WY

Senior

2025-05-25

WY 2025-05-25

View full posting on CareerOneStop → ID: 3fa73cdf9362

Staff Software Engineer - Machine Learning

General Motors · Bismarck, ND

Senior

2025-05-25

ND 2025-05-25

View full posting on CareerOneStop → ID: 0d0a5707011e

Staff Software Engineer - Machine Learning

General Motors · Pierre, SD

Senior

2025-05-25

SD 2025-05-25

View full posting on CareerOneStop → ID: 478571070267

Data Scientist, Product Analytics

Meta · Olympia, WA

Mid-level

2024-12-05

WA 2024-12-05

View full posting on CareerOneStop → ID: 1b3eb089ac01

Data Scientist, Product Analytics

Meta · Olympia, WA

Mid-level

2024-12-05

WA 2024-12-05

View full posting on CareerOneStop → ID: 48f35c309984

Data Scientist, Product Analytics

Meta · Boise, ID

Mid-level

2024-12-05

ID 2024-12-05

View full posting on CareerOneStop → ID: 21df90ba7356

Data Scientist, Product Analytics

Meta · Salem, OR

Mid-level

2024-12-05

OR 2024-12-05

View full posting on CareerOneStop → ID: 80ab85d714a5

Data Scientist, Product Analytics

Meta · Salem, OR

Mid-level

2024-12-05

OR 2024-12-05

View full posting on CareerOneStop → ID: 67366d4ff18f

Data Scientist, Product Analytics

Meta · Helena, MT

Mid-level

2024-12-05

MT 2024-12-05

View full posting on CareerOneStop → ID: 841eae6a75f8

Data Scientist, Product Analytics

Meta · Cheyenne, WY

Mid-level

2024-12-05

WY 2024-12-05

View full posting on CareerOneStop → ID: c188436dfe3f

Data Scientist, Product Analytics

Meta · Cheyenne, WY

Mid-level

2024-12-05

WY 2024-12-05

View full posting on CareerOneStop → ID: 86daa8f395e0

Data Scientist, Product Analytics

Meta · Bismarck, ND

Mid-level

2024-12-05

ND 2024-12-05

View full posting on CareerOneStop → ID: 439ef77721a4

Data Scientist, Product Analytics

Meta · Bismarck, ND

Mid-level

2024-12-05

ND 2024-12-05

View full posting on CareerOneStop → ID: 0f7058cbebcd

Data Scientist, Product Analytics

Meta · Pierre, SD

Mid-level

2024-12-05

SD 2024-12-05

View full posting on CareerOneStop → ID: d16b0f64fe8a

Data Scientist, Product Analytics

Meta · Pierre, SD

Mid-level

2024-12-05

SD 2024-12-05

View full posting on CareerOneStop → ID: 7aa1c62c2041

Data Scientist, Product Analytics

Meta · Olympia, WA

Mid-level

2024-12-03

WA 2024-12-03

View full posting on CareerOneStop → ID: 30c1aa8db12f

Data Scientist, Product Analytics

Meta · Olympia, WA

Mid-level

2024-12-03

WA 2024-12-03

View full posting on CareerOneStop → ID: d848fcc46918

Data Scientist, Product Analytics

Meta · Boise, ID

Mid-level

2024-12-03

ID 2024-12-03

View full posting on CareerOneStop → ID: e45df11201a1

Data Scientist, Product Analytics

Meta · Salem, OR

Mid-level

2024-12-03

OR 2024-12-03

View full posting on CareerOneStop → ID: f547fdb3d4c9

Data Scientist, Product Analytics

Meta · Salem, OR

Mid-level

2024-12-03

OR 2024-12-03

View full posting on CareerOneStop → ID: e46dc8757e1d

Data Scientist, Product Analytics

Meta · Bellevue, WA

Mid-level

2024-10-24

WA 2024-10-24

View full posting on CareerOneStop → ID: dd45c760ed40