Jobs — Data Scientists

(USA) Senior, Data Scientist

Walmart · Bellevue, WA

Senior Master's

2026-06-05

WA 2026-06-05

Requirements

Very good knowledge of the foundations of machine learning and statistics
Experience in Analyzing the Complex Problems and translate it into data science algorithms
Experience in machine learning, supervised and unsupervised and deep learning.
Hands on experience in Computer Visions and NLP. Gen AI, Agentic AI
Experience with big data analytics - identifying trends, patterns, and outliers in large volumes of data
Strong Experience in Python with excellent knowledge of Data Structures
Strong Experience with big data platforms - Hadoop (Hive, Pig, Map Reduce, HQL, Scala, Spark)
Hands on experience with Git
Experience with SQL and relational databases, data warehouse
Bachelors with > 7 years of experience / Master's degree with > 5 years of experience. Educational qualifications should be preferably in Computer Science/Mathematics/Statistics or a related area. Experience should be relevant to the role.
Experience in ecommerce domain.
Experience in R and Julia
Demonstrated success in data science platforms like Kaggle.
_Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications._
Option 1- Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3 years' experience in an analytics related field. Option 2- Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 1 years' experience in an analytics related field. Option 3 - 5 years' experience in an analytics or related field.

Preferred

_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, Master's degree 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, 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.
*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

*Immigration Sponsorship support will NOT be available for this position Join Marketplace Tech to help power a fast-growing, two-sided platform connecting customers with third-party sellers at massive scale. As a Data Scientist, you'll turn complex marketplace data into actionable insights and production-ready models that improve seller success, customer experience, trust & safety, and overall marketplace growth. You'll partner closely with product, engineering, and business teams to define success metrics, run experiments, build predictive and causal solutions, and communicate clear recommendations that drive measurable impact. Immigration Sponsorship support will NOT be available for this
Drive data-derived insights across the wide range of retail divisions by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives
Direct the gathering of data, assessing data validity and synthesizing data into large analytics datasets to support project goals
Utilize big data analytics and advanced data science techniques to identify trends, patterns, and discrepancies in data. Determine additional data needed to support insights
Build and train statistical models and machine learning algorithms for replication for future projects
Communicate recommendations to business partners and influencing future plans based on insights

View full posting on CareerOneStop → ID: 2b56f54b6ce5

Distinguished, Data Scientist

Walmart · Bellevue, WA

Senior Doctorate

2026-06-05

WA 2026-06-05

Requirements

Bachelor's with >20years, Masters > 17yearsOR Ph.D. in Comp Science/Statistics/Mathematics with > 14years of relevant experience. Educational qualifications should be Computer Science/Statistics/Mathematics ora related area.
Experience of acting as a tech lead for > 10 years
_Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications._
Option 1: Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 6 years' experience in an analytics related field. Option 2: Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 3: 8 years' experience in an analytics or related field.

Preferred

_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, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, 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.
*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

As a Distinguished Data Scientist in the Marketplace data sciences team, you'll have the opportunity to -
Drive innovative strategic solutionsfor Marketplaceutilizingadvanced SOTA AI and ML solutions at large scale and atacceleratedpace.
Drive data-derived insights by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives
Work closely with Directors, Sr. Managers of Data Science, and leaders ofArchitecture,Engineering,Product& businessteams to drive the Organizational strategy aroundMarketplace.
Direct the gathering of data, assess datavalidityand synthesize data into large analytics datasets to support project goals
Mentor and guide a setof Data Scientists, Data Analystsacross IDC and UStodrive Marketplace growth and operation efficiencyusing advanced Machine Learning and Gen AI.
Utilize big data analytics and advanced data science techniques toidentifytrends, patterns, and discrepancies in data.Determineadditionaldata needed to support insights
Build and train AI/ML models for replication for future projects
Deploy andmaintainthe data science solutions
Communicate recommendations to business partners and influencefuture plansbased on insights
*Position Responsibility
Consult with product/business stakeholders on algorithmic recommendations and translate insights into actions.
Lead and mentor domain data science teams to deliver ML products on time.
Collaborate cross-functionally to drive end-to-end content improvement.
Research and develop innovative content-improvementsolutions leveragingmultilingual and multimodal foundation models.
Identifycomplex business opportunities solvable with advanced ML/Computer Vision; evaluate and prioritize business cases.
Define success criteria, deliverables, and KPIs; quantify and track business impact of ML products.
Establish model evaluation/testing standards and documentation; guide deployment viaMLOpsbest practices.
Communicate recommendations, influence partners globally, and drive innovation while upholding company values and ethics.

View full posting on CareerOneStop → ID: 7cecdc0d131f

EY-Parthenon - Strategy and Execution - Growth Platforms - AI/ML Engineer - Sr Associate/Consultant

EY · Seattle, WA

Senior Master's

2026-06-05

WA 2026-06-05

Requirements

Outstanding academic performance, with a bachelor's degree and at least 2 years of related work experience; or a graduate degree and approximately 18 months of related work experience.?
Familiarity with multi-modal agent frameworks (LangChain, Haystack, RAG pipelines).
Knowledge in vector databases (e.g., Pinecone, Weaviate, Chroma), retrieval systems, and LLM fine-tuning.
Strong understanding of real-world structured data merging, schema linking, and model evaluation at scale.
Strong understanding of ML workflow including ingesting, analyzing, transforming data, and evaluating results to make meaningful predictions.
Fluency in Python, PyTorch or TensorFlow, with ability to architect APIs around ML models.
Demonstrated experience designing, building, and maintaining ML models, frameworks, and pipelines.
Excellent communication skills, with the ability to convey complex, technical concepts and progress, methodologies, solutioning, and results to business and client stakeholders.
The ability and willingness to travel and work in excess of standard hours when necessary.
*Ideally, you will have
Experience building and deploying AI/ML products or features in a production environment.
Experience working in a startup and/or management/strategy consulting.
Knowledge of how to leverage AI tools in a business setting, including Microsoft Copilot.
Collaborative, problem-solving, and growth-oriented mindset.
*What we look fo
We're interested in passionate leaders with strong vision and a desire to stay on top of trends in the Data Science and Big Data industry. If you have a genuine passion for helping businesses achieve the full potential of their data, this role is for you.

Responsibilities

The EY Growth Platforms AI ML Engineering Senior Associate/Consultant will play a critical role building and maintaining our core advanced analytics platform and serving the technical execution lead for high-visibility client engagements. You'll work with Business leaders and C-level executives to translate business needs into technically executable ML agentic workflows and work alongside a high-performing team of engineers and contractors through end-to-end project lifecycles.
*Skills and attributes for success
Partner with Business and Strategy Leads to translate business needs into executable AI workflows, data pipelines, and client-specific product specifications.
Assist in defining the end-to-end architecture for agents that integrate LLMs, retrieval-augmented generation (RAG), multi-source data ingestion, and analytics components.
Participate in model selection, feature design, embedding strategy, and prompt frameworks (e.g., LangChain, LlamaIndex).
Participate in the design and build robust data pipelines that are scalable, reproducible, and versioned.

View full posting on CareerOneStop → ID: e0e3ba039dcc

EY-Parthenon - Strategy and Execution - Growth Platforms - Data Scientist - Sr Associate/Consultant

EY · Seattle, WA

Senior Master's

2026-06-05

WA 2026-06-05

Requirements

Outstanding academic performance, with a bachelor's degree and at least 2 years of related work experience; or a graduate degree and approximately 18 months of related work experience.?
Experience in data engineering or hybrid data science roles focused on pipeline scalability and schema management.
Familiarity in cloud-native data infrastructure (e.g., GCP/AWS, Snowflake, BigQuery, Databricks, Delta Lake).
Strong SQL/Python/Scala proficiency and experience with orchestration tools (Airflow, dbt).
Experience with merging and reconciling third-party data (public APIs, vendor flat files, dashboards).
Comfort defining semantic layers and mapping unstructured/dirty datasets into usable models for AI/BI use.
Basic understanding of ML/feature pipelines and downstream modeling needs.
The ability and willingness to travel and work in excess of standard hours when necessary.
*Ideally, you will have
Experience working in a startup and/or management/strategy consulting.
Knowledge of how to leverage AI tools in a business setting, including Microsoft Copilot.
Collaborative, problem-solving, and growth-oriented mindset.
*What we look fo
We're interested in passionate leaders with strong vision and a desire to stay on top of trends in the Data Science and Big Data industry. If you have a genuine passion for helping businesses achieve the full potential of their data, this role is for you.

Responsibilities

The EY Growth Platforms Data Scientist Senior Associate/Consultant will play a critical role building and scaling our multi-source data pipelines- sourcing, merging, and transforming data assets that power high-visibility client engagements. This role will participate in building, cleaning, transforming, and enriching data to power AI/ML-driven agents and dashboards, and collaborate with Business leaders and C-level executives to get hands-on experience solving some of the most interesting and mission-critical business questions with data.
*Skills and attributes for success
Lead ingestion and ETL design for structured and semi-structured data (CSV, JSON, APIs, Flat Files).
Understand schema, data quality, and transformation logic for multiple sources on a client-by-client like NAIC, NOAA, Google Trends, EBRI, Cannex, LIMRA, and internal client logs.
Design normalization and joining pipelines across vertical domains (insurance + consumer + economic data).
Build data access layers optimized for ML (feature stores, event streams, vector stores).
Define and enforce standards for data provenance, quality checks, logging, and version control.
Partner with AI/ML and Platform teams to ensure data is ML- and privacy-ready (HIPAA, SOC2, etc.).

View full posting on CareerOneStop → ID: 37cb20019308

Principal, Data Scientist

Walmart · Bellevue, WA

Senior

2026-06-05

WA 2026-06-05

View full posting on CareerOneStop → ID: 424740263d1c

Senior Data Scientist IV - AI Safety

Pacific Northwest National Laboratory · Seattle, WA

Senior

2026-06-05

WA 2026-06-05

View full posting on CareerOneStop → ID: e55139e48c77

Senior Data Scientist IV - Gen AI Development & Evaluation

Pacific Northwest National Laboratory · Seattle, WA

Senior

2026-06-05

WA 2026-06-05

View full posting on CareerOneStop → ID: 2c55c72257d2

Sr. Data Scientist, WW Insurance & Claim

Amazon · Bellevue, WA

Senior

2026-06-05

WA 2026-06-05

View full posting on CareerOneStop → ID: b097fa8e1125

Staff, Data Scientist

Walmart · Bellevue, WA

Senior

2026-06-05

WA 2026-06-05

View full posting on CareerOneStop → ID: 179daa8c99af

Senior Data Scientist IV - AI Safety

Pacific Northwest National Laboratory · Richland, WA

Senior

2026-06-05

WA 2026-06-05

View full posting on CareerOneStop → ID: 63a6eba5652f

Senior Data Scientist IV - Gen AI Development & Evaluation

Pacific Northwest National Laboratory · Richland, WA

Senior

2026-06-05

WA 2026-06-05

View full posting on CareerOneStop → ID: b9f48d4f4bf0

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

(USA) Senior Distinguished I, Data Scientist

Walmart · Bellevue, WA

Senior

2026-06-04

WA 2026-06-04

View full posting on CareerOneStop → ID: d91c06721349

(USA) Staff, Data Scientist

Walmart · Bellevue, WA

Senior

2026-06-04

WA 2026-06-04

View full posting on CareerOneStop → ID: 844c4d5a4ab8

(USA) Staff, Data Scientist

Walmart · Bellevue, WA

Senior

2026-06-04

WA 2026-06-04

View full posting on CareerOneStop → ID: 2141905369f9

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

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

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

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

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

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

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

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

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

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

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

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- 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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Senior Applied Data Scientist

Eliassen Group · Helena, MT

Senior

2026-05-20

MT 2026-05-20

View full posting on CareerOneStop → ID: cb65e1e89c3e

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

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

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

AI Data Scientist Sr.

Sedgwick · Boise, ID

Senior

2026-05-15

ID 2026-05-15

View full posting on CareerOneStop → ID: 093121240dae

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

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, 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

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

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 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

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

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 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

Senior Specialist - Data Science - Fraud Analytics

Ally · Austin, TX

Senior

2026-05-13

TX 2026-05-13

View full posting on CareerOneStop → ID: 3a6d4eeba527

Principal, Data Scientist

Walmart · Bentonville, AR

Senior

2026-05-13

AR 2026-05-13

View full posting on CareerOneStop → ID: 51638ca55141

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

Senior Data Scientist

Fiserv · Alpharetta, GA

Senior

2026-05-13

GA 2026-05-13

View full posting on CareerOneStop → ID: 8bcab11fc9a2

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

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

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

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

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

Senior Data Scientist

Nelnet · Sacramento, CA

Senior

2026-05-12

CA 2026-05-12

View full posting on CareerOneStop → ID: ed4a527e20e2

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 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

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

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

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

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

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

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

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

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

Principal Data Scientist

Maximus · Jefferson City, MO

Senior

2026-05-09

MO 2026-05-09

View full posting on CareerOneStop → ID: 3b69e6f69ec6

Senior AI/ML Engineer

General Motors · Jefferson City, MO

Senior

2026-05-09

MO 2026-05-09

View full posting on CareerOneStop → ID: 88810b777595

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

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

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

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

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

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

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

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

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

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

Sr. Staff Data Scientist

Northrop Grumman · Clearfield, UT

Senior

2026-05-08

UT 2026-05-08

View full posting on CareerOneStop → ID: d5ed5e334bb5

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

Senior Data Scientist

Loyola University Chicago · Chicago, IL

Senior

2026-05-08

IL 2026-05-08

View full posting on CareerOneStop → ID: 925649c43c0a

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

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

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

Lead AI/ML Engineer

TEKsystems · Minneapolis, MN

Senior

2026-05-07

MN 2026-05-07

View full posting on CareerOneStop → ID: 697c682dae95

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

Staff, Data Scientist

Walmart · Bentonville, AR

Senior

2026-05-07

AR 2026-05-07

View full posting on CareerOneStop → ID: 0a317f353efe

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

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

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

Staff AI/ML Engineer

CACI International · Aurora, CO

Senior

2026-05-06

CO 2026-05-06

View full posting on CareerOneStop → ID: b6657e665fa8

Senior, Data Scientist - Workforce Intelligence

Walmart · Bentonville, AR

Senior

2026-05-06

AR 2026-05-06

View full posting on CareerOneStop → ID: a966b9d10c14

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

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

Senior Data Scientist

CRIBL, INC. · Salt Lake City, UT

Senior

2026-05-05

UT 2026-05-05

View full posting on CareerOneStop → ID: 2fcf8e1a9a18

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

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

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

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

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 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

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

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

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

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

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

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

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

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

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

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 Marketing Data Scientist

USAA · Phoenix, AZ

Senior

2026-05-01

AZ 2026-05-01

View full posting on CareerOneStop → ID: c3c3c2481c0e

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

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 Marketing Data Scientist

USAA · Colorado Springs, CO

Senior

2026-05-01

CO 2026-05-01

View full posting on CareerOneStop → ID: dc7129c7a1e1

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Senior Data Scientist

Cribl, Inc · Frankfort, KY

Senior

2026-04-28

KY 2026-04-28

View full posting on CareerOneStop → ID: 40e523e3f6b8

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

(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

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

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

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

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

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

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

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

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

(USA) Distinguished, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-18

AR 2026-04-18

View full posting on CareerOneStop → ID: 50beb9123f89

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

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

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

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) 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

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

(USA) Principal, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-08

AR 2026-04-08

View full posting on CareerOneStop → ID: 12391bdde80b

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

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

(USA) Senior, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-07

AR 2026-04-07

View full posting on CareerOneStop → ID: 066bd154c2f4

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

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

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

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

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

(USA) Staff, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-03

AR 2026-04-03

View full posting on CareerOneStop → ID: 7a534faccc09

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

Principal Data Scientist

Microsoft Corporation · Redmond, WA

Senior

2026-04-01

WA 2026-04-01

View full posting on CareerOneStop → ID: 26466c4c6b3d

Senior Data Scientist

Micron Technology, Inc. · Boise, ID

Senior

2026-04-01

ID 2026-04-01

View full posting on CareerOneStop → ID: 5ba8159c2d13

(USA) Senior, Data Scientist

Walmart · Bentonville, AR

Senior

2026-04-01

AR 2026-04-01

View full posting on CareerOneStop → ID: cb17a8816eea

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

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

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

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

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

Senior, Data Scientist (Pricing)

Walmart · Bentonville, AR

Senior

2026-03-13

AR 2026-03-13

View full posting on CareerOneStop → ID: 3cbcfe3fc4d2

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

Principal, Data Science & Analytics

Microsoft Corporation · Redmond, WA

Senior

2026-03-08

WA 2026-03-08

View full posting on CareerOneStop → ID: fa4b158098d7

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

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

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

Principal Data Scientist

Microsoft Corporation · Redmond, WA

Senior

2026-03-04

WA 2026-03-04

View full posting on CareerOneStop → ID: 2d2633fc04f2

Lead Data Scientist - Safety Alignment

Humana · Olympia, WA

Senior

2026-02-27

WA 2026-02-27

View full posting on CareerOneStop → ID: 1e150ea50b8e

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

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 - 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 - 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 - Senior - Consulting

EY · Salem, OR

Senior

2026-02-06

OR 2026-02-06

View full posting on CareerOneStop → ID: 6465eee93de9

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

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

Senior Machine Learning Engineer

General Motors · Olympia, WA

Senior

2026-01-23

WA 2026-01-23

View full posting on CareerOneStop → ID: f8c3e4b82907

Principal Data Scientist - CoreAI

Microsoft Corporation · Redmond, WA

Senior

2025-12-20

WA 2025-12-20

View full posting on CareerOneStop → ID: e4ae8aa6edc6

Principal Machine Learning Engineer

Microsoft Corporation · Redmond, WA

Senior

2025-12-19

WA 2025-12-19

View full posting on CareerOneStop → ID: 4c2416b5d5e5

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 - 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 - 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 - 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 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

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

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