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Data Scientists

15-2051.00 Bright Outlook $158K
149
postings · Doctorate
Career stage: All Intern (18) Entry-level (23) Mid-level (447) Senior (713) Manager (182) Director (151)
Education: All Bachelor's (52) Master's (77) Doctorate (149)
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Career stage is read from the job title. Use it to find jobs aimed at where you are right now:
  • Intern You can apply while still in school.
  • Entry-level Designed for new graduates.
  • Mid-level Typically expects internship or 2-3 years of experience.
  • Senior Established career role — usually 5+ years experience.
  • Manager Leads a team of engineers, not an early-career role.
  • Director Executive role — typically 10+ years of career experience.
Education is the highest degree the posting explicitly mentions. Postings that don't say are not filtered out — they appear under "All".
AI and Data Science Engineer III
Deloitte · Seattle, WA
Mid-level Doctorate
2026-06-05
Requirements
  • Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
  • 4+ years of experience in data science, analytics, or a related field - with direct experience in client-facing or consulting environments.
  • 4+ years of demonstrated proficiency in SQL for data extraction, transformation, and analysis across relational databases.
  • 4+ years of demonstrated proficiency in Python or R for statistical modeling and data wrangling.
  • 4+ years of hands-on experience with data visualization tools such as Tableau, Power BI, or equivalent platforms.
  • 4+ years of building analytics solutions end-to-end: from data ingestion and modeling to visualization and stakeholder presentation.
  • Ability to travel 0-25%, on average, based on client and project needs.
  • Limited immigration sponsorship may be available
Preferred
  • Advanced degree (MS/PhD) and/or relevant certifications (data science and AI/ML).
  • Experience working with workforce, HR, or human capital data (e.g., headcount, attrition, compensation, organizational network analysis).
  • AI fluency and familiarity with machine learning concepts, large language model applications, or AI-augmented analytics workflows.
  • Economics background or acumen, with the ability to apply labor market economics principles to workforce problems.
  • Experience in analytics product development - building repeatable tools, models, or platforms rather than one-off deliverables.
  • Proficiency in Python or R for statistical modeling and data wrangling.
  • Strong communication skills with the ability to convey complex analytical insights to diverse audiences.
  • 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 $122,000 to $240,500.
  • 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.
Responsibilities
  • Lead the design, development, and delivery of analytics solutions that address complex workforce and human capital challenges for clients across industries.
  • Build and maintain scalable data pipelines, dashboards, and reporting frameworks using SQL and Tableau (or equivalent visualization platforms).
  • Translate ambiguous business problems into structured analytical approaches, communicating findings and recommendations clearly to both technical and non-technical stakeholders.
  • Collaborate across service lines to embed AI-enabled capabilities and emerging data methodologies into client solutions.
  • Support business development efforts including proposals, client presentations, and thought leadership content.
  • Design and deliver intuitive, executive-ready reports and dashboards that make complex workforce data accessible and actionable.
  • Apply economic and statistical reasoning to interpret workforce trends, model scenarios, and support evidence-based decision-making.
  • A successful candidate would possess these skills:
  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeano
  • Ability to meet deadlines
  • Ability to provide clear guidance to others
  • HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.
View full posting on CareerOneStop → ID: 046cdce469aa
Data Scientist Engineer - SFL Scientific
Deloitte · Seattle, WA
Mid-level Doctorate
2026-06-05
Requirements
  • Master's or Ph.D. in a relevant STEM field (Data Science, Computer Science, Engineering, Physics, Mathematics, etc.)
  • 2+ 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)
  • 2+ 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
  • 2+ years of experience deploying and optimizing ML models using tools like Kubernetes, Docker, TensorRT/Triton, RAPIDs, Kubeflow, and MLflow
  • 2+ 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
  • 1+ 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, agent-based tools and services, and GenAI frameworks (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 $95,600 to $188,400.
  • 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: ce298ebdb793
Data Scientist, Finance
Meta · Bellevue, WA
Mid-level Doctorate
2026-06-05
Requirements
  • Bachelor's degree in a directly related field, or equivalent practical experience
  • A minimum of 12 years of work experience in analytics (minimum of 8 years with a Ph.D.)
  • Experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), and/or statistical/mathematical software (e.g., R)
Preferred
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Master's or Ph.D. degree in a quantitative field
  • Experience working in a data science role at a hyperscaler / public cloud and / or a large customer of a public cloud company
  • Experience partnering cross-functionally with a wide range of teams, dealing with ambiguous and presenting technical content in an easy to understand manner to technical and non-technical teams
  • Knowledge of business outcomes and technology investments and experience connecting them to practical models for decision making
Responsibilities
  • Meta is seeking a Data Scientist to join the data science team in the Finance organization that partners very closely with Product, AI, Infrastructure, Finance and other Data Science teams across the company. These teams are building some of the most cutting edge and transformative AI products in the world that are being rolled out to Meta's 3 Billion+ users. Building these products and features requires tens of billions of dollars of capital each year over a sustained period of time. Managing and optimizing the deployment of this vast capital and the allocation of these resources requires a team that has technical expertise in AI and Infrastructure along with a solid understanding of data science, finance and operations. This position will use data and analysis to identify and solve product development's biggest challenges and will require an understanding of how AI and Infrastructure are built, operated and used to serve users. This role will help establish the ROI and company-wide prioritization of such investments and work on solving some of the most important technological problems of our times and also ensure that the company makes efficient investments. As an individual contributor, you will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a high-performing analytics community dedicated to skill development and career growth in analytics and beyond.
  • Work with large and complex data sets to solve a wide array of problems using different analytical and statistical approaches
  • Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to build and maintain end-to-end models for long range planning and strategic decisions
  • Build models to compute and explain Infrastructure OPEX and CAPEX costs at the company, product and resource levels
  • Leverage understanding of AI and Infrastructure to develop point-of-view on ROI of investments in Infrastructure and allocation of Infrastructure resources to various products and software platforms
  • Identify and measure success infrastructure investments through goal setting, forecasting, and monitoring of key metrics to understand trends
  • Help define resource allocation policies that are reasonable and actionable from a technical, operational and financial perspective
  • Work with product, engineering and data science teams to do technical, operational and business impact assessments of re-allocation of resources based on changing business needs, competitive landscape and product roadmaps
  • Maintain lineage of decisions around Infrastructure investments and assumptions under which those decisions were made to drive accountability for outcomes across the company
  • Define, understand, and test opportunities and levers to improve the our models, and drive roadmaps through your insights and recommendations
  • Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
View full posting on CareerOneStop → ID: 5cac8678fb28
Distinguished, Data Scientist
Walmart · Bellevue, WA
Senior Doctorate
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
AIML - ML Engineer, Responsible AI
Apple · Seattle, WA
Mid-level Doctorate
2026-06-04
Requirements
  • Strong engineering skills and experience in writing production-quality code in Python, Swift or other programming languages
  • Background in generative models, natural language processing, LLMs, or diffusion models
  • Experience with failure analysis, quality engineering, or robustness analysis for AI/ML based features
  • Experience working with crowd-based annotations and human evaluations
  • Experience working on explainability and interpretation of AI/ML models
  • Work with highly-sensitive content with exposure to offensive and controversial content
Preferred
  • BS, MS or PhD in Computer Science, Machine Learning, or related fields or an equivalent qualification acquired through other avenues
  • Proven track record of contributing to diverse teams in a collaborative environment
Responsibilities
  • Would you like to play a part in building the next generation of generative AI applications at Apple? We're looking for scientists and engineers to work on ambitious projects that will impact the future of Apple, our products, and the broader world.
  • In this role, you'll have the opportunity to tackle innovative problems in machine learning, particularly focused on generative AI. As a member of the Apple HCMI group, you will be working on Apple's generative models that will power a wide array of new features. Our team is currently working on large generative models for vision and language, with particular interest on safety, robustness, and uncertainty in models.
  • Develop models, tools, metrics, and datasets for assessing and evaluating the safety of generative models over the model deployment lifecycle
  • Develop methods, models, and tools to interpret and explain failures in language and diffusion models
  • Build and maintain human annotation and red teaming pipelines to assess quality and risk of various Apple products
  • Prototype, implement, and evaluate new ML models and algorithms for red teaming LLMs
View full posting on CareerOneStop → ID: 147f72c89925
Data Scientist - Pricing
Microsoft Corporation · Redmond, WA
Mid-level Doctorate
2026-06-04
Requirements
  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.
Preferred
  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • Experience in Python, R, or similar languages
  • Experience with Azure Machine Learning (ML) or equivalent cloud-based ML platforms.
  • Experience working with large-scale data and distributed systems.
  • Experience with yield or revenue management, pricing optimization, or cloud resource allocation.
  • Data Science IC3 - The typical base pay range for this role across the U.S. is USD $102,100.00 - $202,200.00 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $133,800.00 - $219,200.00 per year.
  • Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
Responsibilities
  • Data Analysis & Modeling: Analyze large-scale datasets to identify patterns, trends, and opportunities for improving yield and efficiency.
  • Yield Optimization: Develop machine learning models to optimize resource allocation and pricing strategies.
  • Cross-Functional Collaboration: Partner with business planning, engineering, product management, and finance teams to align yield strategies with business objectives.
  • Experimentation & A/B Testing: Design and execute experiments to validate optimization hypotheses. Build causal inference models (e.g., difference-in-difference, synthetic control) to measure the impact of business decisions.
  • Data Visualization : Develop dashboards and other visuals to monitor key business trends, identify new opportunities, and translate findings to actionable insights.
  • Thought Leadership : Stay current with industry trends in AI, cloud economics, and optimization techniques; share insights and best practices internally.
  • Other : Embody our Culture (https://www.microsoft.com/en-us/about/corporate-values) and Values (https://careers.microsoft.com/us/en/culture)
View full posting on CareerOneStop → ID: 998bf2a4b542
Machine Learning Engineer - News, Books, and Stocks Team
Apple · Seattle, WA
Mid-level Doctorate
2026-06-04
Requirements
  • MS in Machine Learning, Computer Science, or related field. Alternatively, equivalent industry experience to an MS degree is acceptable.
  • At least 2 years of experience shipping machine learning models in products.
  • Strong programming skills in Python, Java, or a related language, and one of the deep learning toolkits such as PyTorch, TensorFlow, or similar.
  • Ability to communicate effectively and collaborate with partner teams.
  • Commitment to encouraging an open and inclusive work environment.
Preferred
  • Ph.D. in Machine Learning, Computer Science, or related field.
  • At least 5 years of experience shipping machine learning models in products.
  • Experience with recommender systems.
  • Experience with text-centric AI/ML (LLMs, document classification, search, etc.)
  • Experience delivering high quality software at scale.
  • Experience designing user-facing machine learning features with interdisciplinary partners.
Responsibilities
  • In a time where the news and book media landscapes are changing by the day, Apple News and Apple Books stand as champions of quality content, expert curation, user privacy, and the judicious use of machine learning. Our lively and brilliant team consists of client and machine learning engineers who embody Apple's values. We inspire, teach, and otherwise enable each other to do the best work of our careers. Our team's outstanding retention rate speaks to our strong culture of respect for our teammates as both engineers and people. Would you like to work on such a team, solving hard problems in machine learning? Terrific! Please join us for the next generation of these apps!
  • Our team is seeking a high-energy and self-driven machine learning engineer who will play a central role in the delivery of scalable services. The team uses machine learning to tackle difficult and complicated problems in the news, books, and stocks domains, including text extraction, named entity recognition, duplicate detection, search, ranking, and much more! As a member of our dynamic group, you'll have the rare and rewarding opportunity to craft upcoming products that will delight and encourage millions of Apple's customers every day!
View full posting on CareerOneStop → ID: c912119310d9
Staff AI/ML Engineer - Future Sensing, Embodied AI
General Motors · Olympia, WA
Senior Doctorate
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
Requirements
  • Bachelor degree and 5 years of work experience in a computer science, engineering, or related field OR Master's degree and 4 years of work experience in a computer science, engineering, or related field OR Ph.D. and 2 years of work experience in a computer science, engineering, or related field"
  • Learning and growth mindset.
  • Customer-focused.
  • Interpersonal, verbal and written communication skills.
  • Must demonstrate proficiency in at least five and mastery in one of the following six areas: data analysis and relational-style query languages; data pipelining and ETL; working with semi structured and unstructured data; a high- level programming language; distributed computing; understanding of healthcare.
  • Proficiency in iterative development practices.
  • Independently delivering or leading the delivery of data engineering solutions for multiple complex analytics or data science projects and products.
  • A track record of independently delivering or leading the delivery of ML engineering capabilities.
  • Experience in Python-based Data Science frameworks (LangChain, LangGraph, LangFuse).
  • Experience in Model evaluation and deployment.
  • Experience in data curation, prep, training, and fine-tuning of Models.
  • Experience in evaluation frameworks
  • Experience in prompt engineering
  • Experience in working with multiple Models
Preferred
  • Master degree in a computational field, or Bachelor degree with significant healthcare experience
  • Understanding PySpark / Databricks to efficiently work with large data sets
  • Azure Cloud Infrastructure / Deployment with emphasis on AI related tooling, Azure ML, Azure OpenAI, etc.
  • Experience in Observability Frameworks and Framework Operationalization.
  • Experience in creation of knowledge graph database (neo4J)
  • Experience in working with Small Language Models or custom Models
  • *Are you being referred to one of our roles? If so, ask your connection at HCSC about our Employee Referral process!
Responsibilities
  • This position is responsible for the engineering work necessary for successful creation, deployment and managing of AI capabilities of the Intelligent Delivery Platform. This includes
  • ensuring data quality,
  • creation of new data pipelines,
  • optimization and management of existing data pipelines,
  • ingestion and curation of data sources for Gen AI purposes (including chunking/embedding strategies for RAG system),
  • AI Agent delivery,
  • Prompt Engineering,
  • selection and configuration of AI-specific tools and platforms
  • management and monitoring of AI models through MLOps tools and model ops practices.
  • To operationalize AI capabilities, they will work closely with larger team who will supplement where traditional application development support is needed.
  • *NOTE: This hybrid role can be located in CHICAGO IL; WAUKEGAN, IL; TULSA, OK; HELENA, MT; ALBUQUERQUE, NM; or RICHARDSON, TX ~ relocation will not be offered; sponsorship is not available.
View full posting on CareerOneStop → ID: 7af06db303cc
Machine Learning Engineering Manager
Indeed · Seattle, WA
Manager Doctorate
2026-06-03
Responsibilities
  • At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
  • As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
  • Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
  • Work to understand, prioritize, and plan the team's work items without external guidance.
  • Ensure delivery of machine learning solutions, set expectations for what can be done and by when, and prioritize incoming projects.
  • Improve existing Agile, ML, and A/B testing processes and develop new ones.
  • Scope projects, gather and improve on requirements, and delegate work effectively.
  • Partner with and provide project direction and feedback to cross-functional peers, including Product Managers, Software Engineers.
  • Remove roadblocks and give individual contributors autonomy and ownership.
  • Brainstorm with teammates about practical experimental design, navigating production codebases, and model development.
  • Be prepared to closely engage and contribute directly to implementation when necessary.
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with a minimum of 3 years experience
  • Demonstrated achievement as a Manager in Machine Learning Engineering, overseeing teams of 3 or more, and addressing intricate, large-scale problems
  • Well-versed in coding (Python, Java, Go, or C++) and experience with SQL Databases like Presto, and data processing frameworks like Spark
  • Have full-stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring
  • Highly effective in coaching Machine Learning Engineers, facilitating qualification enhancement, and fostering career development
View full posting on CareerOneStop → ID: 85c5b878e3fc
Senior Machine Learning Engineer
Indeed · Seattle, WA
Senior Doctorate
2026-06-03
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
Machine Learning Engineering Manager
Indeed · Portland, OR
Manager Doctorate
2026-06-03
Responsibilities
  • At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
  • As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
  • Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
  • Work to understand, prioritize, and plan the team's work items without external guidance.
  • Ensure delivery of machine learning solutions, set expectations for what can be done and by when, and prioritize incoming projects.
  • Improve existing Agile, ML, and A/B testing processes and develop new ones.
  • Scope projects, gather and improve on requirements, and delegate work effectively.
  • Partner with and provide project direction and feedback to cross-functional peers, including Product Managers, Software Engineers.
  • Remove roadblocks and give individual contributors autonomy and ownership.
  • Brainstorm with teammates about practical experimental design, navigating production codebases, and model development.
  • Be prepared to closely engage and contribute directly to implementation when necessary.
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with a minimum of 3 years experience
  • Demonstrated achievement as a Manager in Machine Learning Engineering, overseeing teams of 3 or more, and addressing intricate, large-scale problems
  • Well-versed in coding (Python, Java, Go, or C++) and experience with SQL Databases like Presto, and data processing frameworks like Spark
  • Have full-stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring
  • Highly effective in coaching Machine Learning Engineers, facilitating qualification enhancement, and fostering career development
View full posting on CareerOneStop → ID: 1dab31464fa0
Senior Machine Learning Engineer
Indeed · Portland, OR
Senior Doctorate
2026-06-03
Responsibilities
  • As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to drive value and better customer experiences for our Sourcing product, which connects employers with new talent through AI. This Senior MLE will help us improve our automated outreach quality, building new agentic experiences, and LLMOps reliability and infrastructure.
  • Autonomously deliver ML and AI projects, including prompt development and evaluation, training ML models, building LLM-as-a-Judge capabilities, and building recommendation / ranking systems
  • Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our Sourcing product
  • Estimate potential business impact of AI and ML and balance tradeoffs between delivery velocity and systematic infrastructure investments
  • Collaborate with cross-functional partners, including Machine Learning Engineers, Data Scientists, Software Engineers, Product, and UX designers/researchers
  • Define and implement evaluation, observability, and production monitoring approaches for ML and LLM-based systems.
  • Serve as a trusted partner and communicator for cross-functional and cross-team counterparts, translating technical concepts to facilitate productive collaboration.
  • Mentor other Machine Learning Engineers, Data Scientists, and Software Engineers on the team
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 5 years of related experience; or a Master's degree with a minimum of 3 years of experience; or a PhD without experience
  • Prior success in deploying impactful Machine Learning and/or LLM-based solutions to large-scale production systems
  • Solid knowledge of data structures and algorithms
  • Demonstrated sense of ownership and accountability as a key contributor in the technical and product domains
  • Familiarity with agent orchestration frameworks, LLM observability tools, and prompt optimization techniques (e.g. GEPA)
  • Knowledge of and practical experience working on Deep Learning libraries (like Torch, Tensorflow, etc.) and modern ML/LLM tooling
  • Familiarity with modern ML system design, including evaluation, experimentation, and production monitoring for predictive and LLM-based systems
  • Excellent written and verbal communication, effective with technical and business audiences
View full posting on CareerOneStop → ID: 40587d39cb8e
Machine Learning Engineering Manager
Indeed · Boise, ID
Manager Doctorate
2026-06-03
Responsibilities
  • At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
  • As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
  • Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
  • Work to understand, prioritize, and plan the team's work items without external guidance.
  • Ensure delivery of machine learning solutions, set expectations for what can be done and by when, and prioritize incoming projects.
  • Improve existing Agile, ML, and A/B testing processes and develop new ones.
  • Scope projects, gather and improve on requirements, and delegate work effectively.
  • Partner with and provide project direction and feedback to cross-functional peers, including Product Managers, Software Engineers.
  • Remove roadblocks and give individual contributors autonomy and ownership.
  • Brainstorm with teammates about practical experimental design, navigating production codebases, and model development.
  • Be prepared to closely engage and contribute directly to implementation when necessary.
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with a minimum of 3 years experience
  • Demonstrated achievement as a Manager in Machine Learning Engineering, overseeing teams of 3 or more, and addressing intricate, large-scale problems
  • Well-versed in coding (Python, Java, Go, or C++) and experience with SQL Databases like Presto, and data processing frameworks like Spark
  • Have full-stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring
  • Highly effective in coaching Machine Learning Engineers, facilitating qualification enhancement, and fostering career development
View full posting on CareerOneStop → ID: fa90c2d42649
Senior Machine Learning Engineer
Indeed · Boise, ID
Senior Doctorate
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
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
Machine Learning Engineering Manager
Indeed · Helena, MT
Manager Doctorate
2026-06-03
Responsibilities
  • At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.
  • As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end
  • Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
  • Work to understand, prioritize, and plan the team's work items without external guidance.
  • Ensure delivery of machine learning solutions, set expectations for what can be done and by when, and prioritize incoming projects.
  • Improve existing Agile, ML, and A/B testing processes and develop new ones.
  • Scope projects, gather and improve on requirements, and delegate work effectively.
  • Partner with and provide project direction and feedback to cross-functional peers, including Product Managers, Software Engineers.
  • Remove roadblocks and give individual contributors autonomy and ownership.
  • Brainstorm with teammates about practical experimental design, navigating production codebases, and model development.
  • Be prepared to closely engage and contribute directly to implementation when necessary.
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with a minimum of 3 years experience
  • Demonstrated achievement as a Manager in Machine Learning Engineering, overseeing teams of 3 or more, and addressing intricate, large-scale problems
  • Well-versed in coding (Python, Java, Go, or C++) and experience with SQL Databases like Presto, and data processing frameworks like Spark
  • Have full-stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring
  • Highly effective in coaching Machine Learning Engineers, facilitating qualification enhancement, and fostering career development
View full posting on CareerOneStop → ID: 86c5ccbc5a93
Senior Machine Learning Engineer
Indeed · Helena, MT
Senior Doctorate
2026-06-03
Responsibilities
  • As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to drive value and better customer experiences for our Sourcing product, which connects employers with new talent through AI. This Senior MLE will help us improve our automated outreach quality, building new agentic experiences, and LLMOps reliability and infrastructure.
  • Autonomously deliver ML and AI projects, including prompt development and evaluation, training ML models, building LLM-as-a-Judge capabilities, and building recommendation / ranking systems
  • Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our Sourcing product
  • Estimate potential business impact of AI and ML and balance tradeoffs between delivery velocity and systematic infrastructure investments
  • Collaborate with cross-functional partners, including Machine Learning Engineers, Data Scientists, Software Engineers, Product, and UX designers/researchers
  • Define and implement evaluation, observability, and production monitoring approaches for ML and LLM-based systems.
  • Serve as a trusted partner and communicator for cross-functional and cross-team counterparts, translating technical concepts to facilitate productive collaboration.
  • Mentor other Machine Learning Engineers, Data Scientists, and Software Engineers on the team
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 5 years of related experience; or a Master's degree with a minimum of 3 years of experience; or a PhD without experience
  • Prior success in deploying impactful Machine Learning and/or LLM-based solutions to large-scale production systems
  • Solid knowledge of data structures and algorithms
  • Demonstrated sense of ownership and accountability as a key contributor in the technical and product domains
  • Familiarity with agent orchestration frameworks, LLM observability tools, and prompt optimization techniques (e.g. GEPA)
  • Knowledge of and practical experience working on Deep Learning libraries (like Torch, Tensorflow, etc.) and modern ML/LLM tooling
  • Familiarity with modern ML system design, including evaluation, experimentation, and production monitoring for predictive and LLM-based systems
  • Excellent written and verbal communication, effective with technical and business audiences
View full posting on CareerOneStop → ID: c5d53fff4ef2
Associate Director, Data Science
Chewy Inc. · Bellevue, WA
Director Doctorate
2026-06-03
Requirements
  • Apply advanced mathematics and data science methodologies;
  • Standard machine learning and statistical techniques including predictive models (time series, regression, etc.), classification, forecasting; and
View full posting on CareerOneStop → ID: 78114146d8aa
Senior Staff Research Data Scientist, DevIE
Google · Kirkland, WA
Senior Doctorate
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
Chief Data Scientist - AI Safety
Pacific Northwest National Laboratory · Seattle, WA
Director Doctorate
2026-06-02
Requirements
  • Based in Richland, WA or Seattle, WA with onsite presence required
  • Clearance required (see below for details)
  • Travel may be required for stakeholder engagement, project events, and sponsor reviews.
  • BS/BA and 9+ years of relevant work experience -OR-
  • MS/MA and 7+ years of relevant work experience -OR-
  • PhD with 5+ year of relevant experience
  • U.S. Citizenship
  • Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
  • As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
  • For foreign national candidates:
  • If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
  • Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
  • *Rockstar Rewards
Preferred
  • Advanced degree in computer science, engineering, data science, mathematics, or a related discipline.
  • Active DOE Q or TS/SCI clearance and ability to maintain such clearance.
  • Demonstrated impact in AI Safety (e.g., peer-reviewed publications, recognized awards, contributions to community standards).
  • National reputation in AI Safety, frontier model evaluation, trustworthy AI, secure machine learning operations, or related mission relevant technical areas.
  • Familiarity with agentic AI safety (tool-use governance, retrieval hygiene, autonomous decision workflows) and evaluation of multi-step reasoning systems.
  • Experience developing and applying cutting edge AI/ML in national security environments, with an understanding of mission needs and operational constraints.
  • Experience serving as PI or project manager on multi-institution R&D efforts.
  • Strong record of securing external funding, managing research portfolios, and initiating new R&D programs in applied AI or AI Safety domains.
  • Experience working with sponsors such as DOE, NNSA, DoD, DHS, or other mission agencies, with the ability to help shape strategic research investments.
  • Proven ability to communicate complex technical concepts to diverse audiences across government, industry, and academia.
Responsibilities
  • Our AI & Data Analytics division is seeking a Chief Data Scientist with deep expertise in data science and experience in AI Safety for national security missions. The selected candidate will lead large, multi-year research and development programs within the AI and Data Analytics Division, which includes over 400 staff specializing in data science, applied mathematics, advanced analytic architectures, software engineering, and human-centered computing. We support PNNL's mission by contributing to impactful, mission-focused applied R&D projects that help tackle national security challenges. This role requires deep technical expertise and the ability to translate emerging research into mission-ready capabilities
  • The Chief Data Scientist will shape national technical direction, engage directly with sponsors and senior leadership, and serve as a strategic partner in aligning PNNL's AI safety portfolio with evolving mission and policy requirements. This individual will guide technical direction, mentor interdisciplinary teams, and collaborate closely with software engineers to transition cutting edge research into field-ready capabilities. In addition to leading research efforts, the Chief Data Scientist will serve as a key interface with sponsors and stakeholders, leveraging domain expertise to align PNNL's research agenda with evolving mission requirements.
  • The chosen candidate will have the unique opportunity to drive real-world impact at mission tempo while supporting PNNL's mission to tackle grand challenges through science, technology, and innovation. Key responsibilities will include:
  • Strategic Leadership and Vision:
  • Shape and execute forward-looking strategies for advancing AI Safety research, evaluation methodologies, and trustworthy deployment practices within PNNL's national security mission space.
  • Partner with government sponsors as a senior technical leader, translating evolving mission priorities and operational risk considerations into actionable research direction and investment opportunities.
  • Lead high-visibility proposal development to help shape national investment in frontier-model safety, agentic AI governance, secure machine learning operations, and evaluation infrastructure.
  • Scientific and Technical Leadership:
  • Lead nationally visible AI Safety programs, ensuring technical excellence, sponsor alignment, risk-informed execution, and timely delivery of impactful results.
  • Serve as a senior technical leader in AI Safety, guiding approaches for evaluating, testing, and characterizing the behavior, risks, and emergent properties of AI models including but not limited to large language models, multimodal models, and agentic AI systems.
  • Provide technical leadership that supports interdisciplinary teams, helping shape research methodologies, data science and engineering best practices, and evaluation strategies while overseeing end-to-end analytic workflows.
  • Build and sustain collaborations across DOE laboratories, federal agencies, academia, and industry to accelerate innovation and deliver integrated, mission-aligned AI Safety capabilities.
  • Partner with software engineering and operational teams to transition research outputs into secure, scalable real-world systems that support national security missions.
  • External Influence & National Representation:
  • Represent PNNL as a senior AI Safety expert in technical exchanges, working groups, and high-impact national and international forums.
  • Publish influential research, contribute to emerging standards, and help shape national discourse on AI Safety.
  • Communicate PNNL's AI capabilities and mission relevance to external stakeholders, articulating use cases, technical solutions, and emerging challenges within the broader national security landscape.
  • Mentorship & Workforce Development:
  • Support the technical and professional development of junior through senior researchers, offering guidance on research challenges, technical leadership skills, and effective collaboration practices.
  • Contribute to an inclusive and learning-oriented environment that encourages scientific rigor, safety-first innovation, and high-impact interdisciplinary work.
  • Collaborate with other senior researchers to strengthen PNNL's AI Safety workforce through mentorship, knowledge sharing, and community building.
  • *Read more about the AIDA division! (https://www.pnnl.gov/ai-and-data-analytics)
View full posting on CareerOneStop → ID: 96cc105ee0f6
Chief Data Scientist - AI Safety
Pacific Northwest National Laboratory · Richland, WA
Director Doctorate
2026-06-02
Requirements
  • Based in Richland, WA or Seattle, WA with onsite presence required
  • Clearance required (see below for details)
  • Travel may be required for stakeholder engagement, project events, and sponsor reviews.
  • BS/BA and 9+ years of relevant work experience -OR-
  • MS/MA and 7+ years of relevant work experience -OR-
  • PhD with 5+ year of relevant experience
  • U.S. Citizenship
  • Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
  • As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
  • For foreign national candidates:
  • If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
  • Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
  • *Rockstar Rewards
Preferred
  • Advanced degree in computer science, engineering, data science, mathematics, or a related discipline.
  • Active DOE Q or TS/SCI clearance and ability to maintain such clearance.
  • Demonstrated impact in AI Safety (e.g., peer-reviewed publications, recognized awards, contributions to community standards).
  • National reputation in AI Safety, frontier model evaluation, trustworthy AI, secure machine learning operations, or related mission relevant technical areas.
  • Familiarity with agentic AI safety (tool-use governance, retrieval hygiene, autonomous decision workflows) and evaluation of multi-step reasoning systems.
  • Experience developing and applying cutting edge AI/ML in national security environments, with an understanding of mission needs and operational constraints.
  • Experience serving as PI or project manager on multi-institution R&D efforts.
  • Strong record of securing external funding, managing research portfolios, and initiating new R&D programs in applied AI or AI Safety domains.
  • Experience working with sponsors such as DOE, NNSA, DoD, DHS, or other mission agencies, with the ability to help shape strategic research investments.
  • Proven ability to communicate complex technical concepts to diverse audiences across government, industry, and academia.
Responsibilities
  • Our AI & Data Analytics division is seeking a Chief Data Scientist with deep expertise in data science and experience in AI Safety for national security missions. The selected candidate will lead large, multi-year research and development programs within the AI and Data Analytics Division, which includes over 400 staff specializing in data science, applied mathematics, advanced analytic architectures, software engineering, and human-centered computing. We support PNNL's mission by contributing to impactful, mission-focused applied R&D projects that help tackle national security challenges. This role requires deep technical expertise and the ability to translate emerging research into mission-ready capabilities
  • The Chief Data Scientist will shape national technical direction, engage directly with sponsors and senior leadership, and serve as a strategic partner in aligning PNNL's AI safety portfolio with evolving mission and policy requirements. This individual will guide technical direction, mentor interdisciplinary teams, and collaborate closely with software engineers to transition cutting edge research into field-ready capabilities. In addition to leading research efforts, the Chief Data Scientist will serve as a key interface with sponsors and stakeholders, leveraging domain expertise to align PNNL's research agenda with evolving mission requirements.
  • The chosen candidate will have the unique opportunity to drive real-world impact at mission tempo while supporting PNNL's mission to tackle grand challenges through science, technology, and innovation. Key responsibilities will include:
  • Strategic Leadership and Vision:
  • Shape and execute forward-looking strategies for advancing AI Safety research, evaluation methodologies, and trustworthy deployment practices within PNNL's national security mission space.
  • Partner with government sponsors as a senior technical leader, translating evolving mission priorities and operational risk considerations into actionable research direction and investment opportunities.
  • Lead high-visibility proposal development to help shape national investment in frontier-model safety, agentic AI governance, secure machine learning operations, and evaluation infrastructure.
  • Scientific and Technical Leadership:
  • Lead nationally visible AI Safety programs, ensuring technical excellence, sponsor alignment, risk-informed execution, and timely delivery of impactful results.
  • Serve as a senior technical leader in AI Safety, guiding approaches for evaluating, testing, and characterizing the behavior, risks, and emergent properties of AI models including but not limited to large language models, multimodal models, and agentic AI systems.
  • Provide technical leadership that supports interdisciplinary teams, helping shape research methodologies, data science and engineering best practices, and evaluation strategies while overseeing end-to-end analytic workflows.
  • Build and sustain collaborations across DOE laboratories, federal agencies, academia, and industry to accelerate innovation and deliver integrated, mission-aligned AI Safety capabilities.
  • Partner with software engineering and operational teams to transition research outputs into secure, scalable real-world systems that support national security missions.
  • External Influence & National Representation:
  • Represent PNNL as a senior AI Safety expert in technical exchanges, working groups, and high-impact national and international forums.
  • Publish influential research, contribute to emerging standards, and help shape national discourse on AI Safety.
  • Communicate PNNL's AI capabilities and mission relevance to external stakeholders, articulating use cases, technical solutions, and emerging challenges within the broader national security landscape.
  • Mentorship & Workforce Development:
  • Support the technical and professional development of junior through senior researchers, offering guidance on research challenges, technical leadership skills, and effective collaboration practices.
  • Contribute to an inclusive and learning-oriented environment that encourages scientific rigor, safety-first innovation, and high-impact interdisciplinary work.
  • Collaborate with other senior researchers to strengthen PNNL's AI Safety workforce through mentorship, knowledge sharing, and community building.
  • *Read more about the AIDA division! (https://www.pnnl.gov/ai-and-data-analytics)
View full posting on CareerOneStop → ID: efac35705ba0
Director, Marketing Data Science
Meta · Seattle, WA
Director Doctorate
2026-06-02
Requirements
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience, Master's degree preferred
  • 10+ years of work experience in data science or decision science (or 8+ years experience with a Ph.D.) supporting a Marketing function
  • Advanced experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and statistical/mathematical software (e.g. R)
  • Experience leading the building of statistical/computational tools in support of marketing functions
  • Advanced knowledge of marketing analytics, survey design, and statistical methods
  • Very comfortable personally using AI tools and transforming organizations to be AI-Native
  • Strong leadership skills, with the ability to operate autonomously and manage cross-functional teams
  • Excellent stakeholder management and communication skills, with experience presenting to executive leadership
Preferred
  • Previous experience in Public Affairs Marketing or Public Opinion Polling
  • 3+ years in Corporate Communications Analytics (e.g. social listening)
  • Expertise in high-frequency measurement models, campaign optimization, and real-time reporting
Responsibilities
  • We are seeking a highly experienced Senior Marketing Data Science Leader to drive measurement, analytics, and strategy across Corporate, Public Affairs, AI Marketing and Corporate Communications at Meta. This role is pivotal in supporting high-impact marketing campaigns, developing innovative measurement frameworks, and collaborating with executive leadership to optimize marketing effectiveness.
  • Lead Measurement & Analytics: Oversee the measurement of campaigns, including AI Marketing, Corporate Marketing, and Public Affairs. Develop and refine high-frequency measurement models for real-time campaign optimization and reporting.
  • Strategic Campaign Support: Partner with VPs and Directors to design, execute, and evaluate marketing campaigns across multiple regions and business units. Lead the development of holdout strategies and funnel analysis to validate campaign effectiveness.
  • Innovation & Efficiency: Invent and implement new measurement programs to consolidate trackers, enhance efficiency, and optimize resource allocation.
  • Cross-Functional Leadership: Operate with autonomy, managing a team of ~15 and collaborating with cross-functional partners in Product, Research, and Corporate Marketing. Support recruiting and interview process improvements for Marketing Data Science.
  • Stakeholder Engagement: Serve as a direct report to the VP, Marketing Data Science, and engage with peers at the Director level. Present findings and recommendations to senior leadership, influencing strategic decisions.
  • Community & Thought Leadership: Amplify the impact of Meta's Analytics community through blog contributions, paid media strategies, and recruiting initiatives.
View full posting on CareerOneStop → ID: 745721090f79
Sr. Machine Learning Engineer, Monetization Engineering
Pinterest, Inc. · Seattle, WA
Senior Doctorate
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
Data Scientist
Deloitte · Portland, OR
Mid-level Doctorate
2026-05-30
Requirements
  • Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
  • 5+ Years of Experience in a Data Science or Machine Learning role.
  • 5+ Years of Experience Proficiency in programming languages such as Python or R.
  • 5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
  • 5+ Years of Experience with data manipulation and analysis libraries like pandas and NumPy
  • Limited immigration sponsorship may be available
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Master's or Ph.D. in a relevant field.
  • Experience with big data technologies like Spark or Hadoop.
  • Experience with deep learning frameworks like TensorFlow or PyTorch.
  • Familiarity with cloud platforms such as AWS, Azure, or GCP.
  • Experience with data visualization tools like Tableau or Power BI.
  • Analytical/ Decision Making Responsibilities
  • Analytical ability to manage multiple projects and prioritize tasks into manageable work products
  • Can operate independently or with minimum supervision
  • Excellent Written and Communication Skills
  • Ability to deliver technical demonstrations
  • The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400-207,800
  • You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Responsibilities
  • Work with stakeholders to identify business problems and formulate them as data science challenges.
  • Collect, clean, and explore large datasets to uncover trends and patterns.
  • Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
  • Validate and deploy models into production environments.
  • Communicate findings and insights to technical and non-technical audiences through data visualization and presentations.
  • Stay up to date with the latest trends and technologies in data science and machine learning.
  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeano
  • Ability to meet deadlines
  • Ability to provide clear guidance to others
  • Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
  • Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
  • AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
  • Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.
View full posting on CareerOneStop → ID: fb47222db27e
Data Scientist
Deloitte · Seattle, WA
Mid-level Doctorate
2026-05-30
Requirements
  • Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
  • 5+ Years of Experience in a Data Science or Machine Learning role.
  • 5+ Years of Experience Proficiency in programming languages such as Python or R.
  • 5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
  • 5+ Years of Experience with data manipulation and analysis libraries like pandas and NumPy
  • Limited immigration sponsorship may be available
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Master's or Ph.D. in a relevant field.
  • Experience with big data technologies like Spark or Hadoop.
  • Experience with deep learning frameworks like TensorFlow or PyTorch.
  • Familiarity with cloud platforms such as AWS, Azure, or GCP.
  • Experience with data visualization tools like Tableau or Power BI.
  • Analytical/ Decision Making Responsibilities
  • Analytical ability to manage multiple projects and prioritize tasks into manageable work products
  • Can operate independently or with minimum supervision
  • Excellent Written and Communication Skills
  • Ability to deliver technical demonstrations
  • The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400-207,800
  • You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Responsibilities
  • Work with stakeholders to identify business problems and formulate them as data science challenges.
  • Collect, clean, and explore large datasets to uncover trends and patterns.
  • Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
  • Validate and deploy models into production environments.
  • Communicate findings and insights to technical and non-technical audiences through data visualization and presentations.
  • Stay up to date with the latest trends and technologies in data science and machine learning.
  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeano
  • Ability to meet deadlines
  • Ability to provide clear guidance to others
  • Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
  • Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
  • AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
  • Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.
View full posting on CareerOneStop → ID: 40c16c089c03
Data Scientist
Deloitte · Bellevue, WA
Mid-level Doctorate
2026-05-30
Requirements
  • Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
  • 5+ Years of Experience in a Data Science or Machine Learning role.
  • 5+ Years of Experience Proficiency in programming languages such as Python or R.
  • 5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
  • 5+ Years of Experience with data manipulation and analysis libraries like pandas and NumPy
  • Limited immigration sponsorship may be available
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Master's or Ph.D. in a relevant field.
  • Experience with big data technologies like Spark or Hadoop.
  • Experience with deep learning frameworks like TensorFlow or PyTorch.
  • Familiarity with cloud platforms such as AWS, Azure, or GCP.
  • Experience with data visualization tools like Tableau or Power BI.
  • Analytical/ Decision Making Responsibilities
  • Analytical ability to manage multiple projects and prioritize tasks into manageable work products
  • Can operate independently or with minimum supervision
  • Excellent Written and Communication Skills
  • Ability to deliver technical demonstrations
  • The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400-207,800
  • You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Responsibilities
  • Work with stakeholders to identify business problems and formulate them as data science challenges.
  • Collect, clean, and explore large datasets to uncover trends and patterns.
  • Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
  • Validate and deploy models into production environments.
  • Communicate findings and insights to technical and non-technical audiences through data visualization and presentations.
  • Stay up to date with the latest trends and technologies in data science and machine learning.
  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeano
  • Ability to meet deadlines
  • Ability to provide clear guidance to others
  • Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
  • Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
  • AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
  • Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.
View full posting on CareerOneStop → ID: b2b19730a972
Machine Learning Research Scientist - Health AIML
Apple · Seattle, WA
Mid-level Doctorate
2026-05-30
Requirements
  • PhD in Computer Science/Engineering, Machine Learning, Statistics, Mathematics or related field.
  • Industry work experience.
  • Experience landing contributions to major LLM training runs.
  • Proven track record of publishing SOTA.
  • Strong skills with deep learning frameworks such as PyTorch, JAX, or TensorFlow.
Preferred
  • Experience in training and evaluating multimodal models.
  • Understand of time-series modeling, self-supervised learning, and cross-modal training.
  • Ability to thoroughly evaluate and improve deep learning architectures in a self-directed fashion.
  • Motivated by safely deploying LLMs in the health and fitness space.
Responsibilities
  • The Health AIML team is at the forefront of machine learning and health science at Apple. We are a close-knit team of research scientists, software engineers and machine learning engineers passionate about delivering innovative technologies that impact millions of users. We are looking for a Machine Learning Research Scientist with strong dedication to solving real-world problems in health and fitness that enrich our customers' lives.
  • We're developing next-generation multimodal models to create intelligent health and fitness experiences. This role requires someone with strong expertise in large multimodal models to work at the intersection of AI and health to build foundational models that scale to billions of users worldwide. Your work will shape the future of health and fitness technologies at Apple. We are looking for a senior researcher to guide multimodality research. You will focus on the development of foundational technology that enables models to understand health and fitness data.
View full posting on CareerOneStop → ID: 49ac6db33d5f
Principal Machine Learning Engineer, Content ML, Level 7
Snap Inc. · Seattle, WA
Senior Doctorate
2026-05-30
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
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
Data Scientist
Deloitte · Boise, ID
Mid-level Doctorate
2026-05-30
Requirements
  • Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
  • 5+ Years of Experience in a Data Science or Machine Learning role.
  • 5+ Years of Experience Proficiency in programming languages such as Python or R.
  • 5+ Years of Experience with Strong knowledge of machine learning techniques and algorithms.
  • 5+ Years of Experience with data manipulation and analysis libraries like pandas and NumPy
  • Limited immigration sponsorship may be available
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Master's or Ph.D. in a relevant field.
  • Experience with big data technologies like Spark or Hadoop.
  • Experience with deep learning frameworks like TensorFlow or PyTorch.
  • Familiarity with cloud platforms such as AWS, Azure, or GCP.
  • Experience with data visualization tools like Tableau or Power BI.
  • Analytical/ Decision Making Responsibilities
  • Analytical ability to manage multiple projects and prioritize tasks into manageable work products
  • Can operate independently or with minimum supervision
  • Excellent Written and Communication Skills
  • Ability to deliver technical demonstrations
  • The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400-207,800
  • You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Responsibilities
  • Work with stakeholders to identify business problems and formulate them as data science challenges.
  • Collect, clean, and explore large datasets to uncover trends and patterns.
  • Develop and train machine learning models to solve problems such as prediction, classification, and clustering.
  • Validate and deploy models into production environments.
  • Communicate findings and insights to technical and non-technical audiences through data visualization and presentations.
  • Stay up to date with the latest trends and technologies in data science and machine learning.
  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeano
  • Ability to meet deadlines
  • Ability to provide clear guidance to others
  • Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
  • Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
  • AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
  • Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.
View full posting on CareerOneStop → ID: 9f4391ee3526
Staff Machine Learning Engineer, AI Research
Cribl, Inc · Helena, MT
Senior Doctorate
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
Data Scientist I, PXT Central Science
Amazon · Bellevue, WA
Entry-level Doctorate
2026-05-29
Requirements
  • 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
  • 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Preferred
  • Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
  • Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
  • Experience working with or evaluating AI systems
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication
Responsibilities
  • Own the design, development, and maintenance of scalable models and prototypes leveraging statistical, machine learning, or GenAI methodologies to enhance employee experience.
  • Partner with scientists, engineers, and product leaders to solve for employee experience defects using scientific approaches, building new services and tools that deliverable measurable impact.
  • Author and maintain detailed technical documentation related to the projects you drive.
  • Communicate results to diverse audiences of varying technical background with effective writing, visualizations, and presentations
  • Stay current with emerging methods and technologies, and implement them strategically to amplify the team's impact.
View full posting on CareerOneStop → ID: 4295c5f82a8c
Data Scientist I, PXT Central Science
Amazon · Seattle, WA
Entry-level Doctorate
2026-05-29
Requirements
  • 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
  • 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Preferred
  • Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
  • Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
  • Experience working with or evaluating AI systems
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication
Responsibilities
  • Own the design, development, and maintenance of scalable models and prototypes leveraging statistical, machine learning, or GenAI methodologies to enhance employee experience.
  • Partner with scientists, engineers, and product leaders to solve for employee experience defects using scientific approaches, building new services and tools that deliverable measurable impact.
  • Author and maintain detailed technical documentation related to the projects you drive.
  • Communicate results to diverse audiences of varying technical background with effective writing, visualizations, and presentations
  • Stay current with emerging methods and technologies, and implement them strategically to amplify the team's impact.
View full posting on CareerOneStop → ID: 96c7b1b6f413
Machine Learning Engineer, Level 4
Snap Inc. · Seattle, WA
Mid-level Doctorate
2026-05-29
Requirements
  • Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
  • 3+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field
  • Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning
Preferred
  • Advanced degree in computer science or related field
  • Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks
  • Experience working with machine learning, ranking infrastructures, and system design
Responsibilities
  • Build and deploy machine learning models that power core products, serving millions of Snapchatters
  • Apply modern ML techniques to solve large-scale, real-world problems
  • Own the full ML lifecycle from data analysis to production deployment
  • Partner with cross-functional teams to prototype and launch ML-driven features
  • Utilize AI tools to design and ship scalable services while upholding rigorous standards for code correctness, security, and production
  • Knowledge, Skills & Abilities:
  • Strong understanding of machine learning approaches and algorithms
  • Able to prioritize duties and work well on your own
  • Ability to work with both internal and external partners
  • Skilled at solving open ambiguous problems
  • Strong collaboration and mentorship skills
  • Proficiency in, or a strong aptitude for, leveraging AI tools to streamline development, paired with the critical judgment to audit generated output for architectural integrity, performance bottlenecks, and security risks
  • Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices
View full posting on CareerOneStop → ID: 3c9d2da8f510
Machine Learning Engineer, Level 4
Snap Inc. · Bellevue, WA
Mid-level Doctorate
2026-05-29
Requirements
  • Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
  • 3+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field
  • Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning
Preferred
  • Advanced degree in computer science or related field
  • Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks
  • Experience working with machine learning, ranking infrastructures, and system design
Responsibilities
  • Build and deploy machine learning models that power core products, serving millions of Snapchatters
  • Apply modern ML techniques to solve large-scale, real-world problems
  • Own the full ML lifecycle from data analysis to production deployment
  • Partner with cross-functional teams to prototype and launch ML-driven features
  • Utilize AI tools to design and ship scalable services while upholding rigorous standards for code correctness, security, and production
  • Knowledge, Skills & Abilities:
  • Strong understanding of machine learning approaches and algorithms
  • Able to prioritize duties and work well on your own
  • Ability to work with both internal and external partners
  • Skilled at solving open ambiguous problems
  • Strong collaboration and mentorship skills
  • Proficiency in, or a strong aptitude for, leveraging AI tools to streamline development, paired with the critical judgment to audit generated output for architectural integrity, performance bottlenecks, and security risks
  • Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices
View full posting on CareerOneStop → ID: 357ea433c4b5
Principal Machine Learning Engineer
Cisco · Bellevue, WA
Senior Doctorate
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
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
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
Principal Engineer, Search and AI Infrastructure, Machine Learning Platform & Infrastructure
Apple · Seattle, WA
Senior Doctorate
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

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

View full posting on CareerOneStop → ID: af0480568034
Business Data Scientist, Ads Marketing Analytics
Google · Kirkland, WA
Mid-level Doctorate
2026-05-28
Requirements
  • Master's degree in a quantitative field (Statistics, Mathematics, Data Science, Bioinformatics, Economics, etc.) or equivalent practical experience
  • 3 years of experience in a data science field.
  • Experience with statistical software (e.g., R, Python, MATLAB) and database languages (i.e., SQL).
  • Experience using analytics to solve product or business problems, querying databases or statistical analysis.
Preferred
  • PhD in Statistics or related quantitative discipline.
  • 2 years of experience, including statistical data analysis such as generalized linear models, multivariate analysis, clustering/segmentation and sampling methods.
  • Experience in controlled experiment design and causal inference methods.
  • Ability to prioritize requests and partner well in an environment with competing demands from stakeholders.
  • Ability to convince business stakeholders and communicate analysis insights to non-technical audiences and willingness to both teach others and learn new techniques.
  • Excellent communication and team-work including problem-solving skills.
Responsibilities
  • Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.
  • Google Ads Marketing helps advertisers of all sizes succeed with digital marketing. In this role, you will work with a team to advance marketing science for customers using Google's advertising solutions. This unique opportunity applies Data Science tools to accelerate Ads business growth, working cross-functionally with Sales, Marketing, and Product teams.
  • As a Data Scientist on this team, you will perform deep data analytics, drive experimentation and measurement, and advance machine learning modeling to support global marketing programs.
  • Collaborating with a multidisciplinary team of marketers, product managers, data scientists, and engineers, you will leverage underlying data to align on key metrics and methodologies. Your insights will enable marketers to develop highly effective programs. Using core Data Science expertise, you will design, prototype, and build scalable analysis pipelines to support campaigns. You will perform analytics, execute experimentation, and conduct incrementality measurement to inform strategic decisions across the entire Ads Marketing lifecycle-from acquisition and onboarding to growth and retention.
  • You will build investigative frameworks and measurement capabilities to generate data-driven insights that drive business growth. You will effectively communicate your investigative results to marketing partners and leadership to inform critical decision-making.
  • The US base salary range for this full-time position is $138,000-$198,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
  • Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
  • Work with large, complex data sets. Solve analysis problems, applying advanced investigative methods (such as statistical and machine learning models) as needed. Conduct analysis that includes problem formulation, data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
  • Design and analyze controlled experiments or counterfactual causal inference studies to examine the incremental impact of Ads marketing programs.
  • Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed.
  • Interact cross-functionally, making business recommendations (e.g. cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
  • Develop and automate reports, iteratively build and prototype dashboards to provide insights at scale, solving for business priorities.
  • Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
View full posting on CareerOneStop → ID: 8bedd46a44c4
AI/ML Engineer
Raft LLC · Tacoma, WA
Mid-level Doctorate
2026-05-28
Requirements
  • 3+ years of relevant hands-on experience, or a PhD in a related field with demonstrated practical application
  • Practical experience in Machine Learning models and Software Engineering
  • A passion for (and track record of) innovation, an interest in exploring and leveraging new data modalities, and working across interdisciplinary teams
  • Experience building and maintaining machine learning platforms and pipelines
  • Experience in building machine learning models, and
  • Experience in using data processing frameworks (Apache Spark preferred)
  • Practical programming and scripting skills (Python preferred)
  • Fast learner, analytical thinker, creative, hands-on, strong communication skills
  • Able to work both independently and as part of a team
  • Excellent problem-solving skills and attention to detail.
  • Proven experience with modern software development and engineering practices including scrum/agile, Git, and DevOps
  • Obtain Security+ within the first 90 days of employment with Raft
  • Ability to obtaina Top Secret clearance with potential for SCI
Preferred
  • Publications or GitHub repos showcasing your skills
Education
  • Annual budget for your tech/gadgets needs
  • Generous Referral Bonuses
  • Annual budget for your tec
Responsibilities
  • *AI/ML Engineer,
  • you will collaborate with a cross-functional data team comprising of DevSecOps engineers, Product Owners, Data Engineers and Data Scientists. Your primary responsibility will be to develop machine learning models that are integral to a larger pipeline delivering value to our end customers.
View full posting on CareerOneStop → ID: 754c9024cb6a
Associate AI/ML Engineer
Raft LLC · Tacoma, WA
Entry-level Doctorate
2026-05-28
Requirements
  • 1+ years of relevant hands-on experience, or a PhD in a related field with demonstrated practical application
  • Practical experience in Machine Learning models and Software Engineering
  • A passion for (and track record of) innovation, an interest in exploring and leveraging new data modalities, and working across interdisciplinary teams
  • Experience building and maintaining machine learning platforms and pipelines
  • Experience in building machine learning models, and
  • Experience in using data processing frameworks (Apache Spark preferred)
  • Practical programming and scripting skills (Python preferred)
  • Fast learner, analytical thinker, creative, hands-on, strong communication skills
  • Able to work both independently and as part of a team
  • Excellent problem-solving skills and attention to detail.
  • Proven experience with modern software development and engineering practices including scrum/agile, Git, and DevOps
  • Obtain Security+ within the first 90 days of employment with Raft
  • Ability to obtaina Top Secret clearance with potential for SCI
Preferred
  • Publications or GitHub repos showcasing your skills
Education
  • Annual budget for your tech/gadgets needs
  • Generous Referral Bonuses
Responsibilities
  • *AI/ML Engineer,
  • you will collaborate with a cross-functional data team comprising of DevSecOps engineers, Product Owners, Data Engineers and Data Scientists. Your primary responsibility will be to develop machine learning models that are integral to a larger pipeline delivering value to our end customers.
View full posting on CareerOneStop → ID: 846be6e0254d
Staff Machine Learning Engineer, Search Ranking
Snap Inc. · Bellevue, WA
Senior Doctorate
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
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 Science Manager, Gen AI - SFL Scientific
Deloitte · Seattle, WA
Manager Doctorate
2026-05-23
Requirements
  • Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
  • 6+ years of experience working in data science, data engineering, software engineering, or MLOps
  • 6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
  • 6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
  • 6+ years of experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms
  • 4+ years of experience managing teams and delivering complex and critical projects
  • Live within commuting distance to one of Deloitte's consulting offices
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available
Preferred
  • Experience with cloud deployment (AWS, Azure, GCP), such as building and scaling in AWS SageMaker or Azure ML Studio
  • Experience with developing and testing GenAI solutions
  • Experience in a client-facing role or internal AI product development role
  • Highly proficient written and verbal skills to support briefings, proposals, technical sprint plans, solution reports, progress updates, and executive presentations
  • The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.
  • You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
View full posting on CareerOneStop → ID: b49278c50cf0
Data Scientist
Actalent · Seattle, WA
Mid-level Doctorate
2026-05-23
Requirements
  • Hands-on expertise with cutting-edge molecular biology, microbiology, and/or biochemistry methods and concepts.
  • Familiarity with data analysis tools and methodologies commonly used in modern laboratory data analysis.
  • 5+ years of experience as a data scientist or in a similar role involving data extraction, analysis, statistical modeling, and communication.
  • 5+ years of experience with data querying languages such as SQL.
  • 5+ years of experience with scripting languages such as Python.
  • 5+ years of experience with statistical or mathematical software such as R, SAS, or MATLAB.
  • Experience with statistical models, including multinomial logistic regression.
  • Experience building and working with data pipelines.
  • Demonstrated ability to work successfully within an entrepreneurial environment.
  • Excellent organizational skills with strong attention to detail and meticulous record keeping.
  • Strong verbal and written communication skills for technical and non-technical audiences.
  • Knowledge of safety procedures related to operation of laboratory equipment and handling of chemical and biological hazards.
  • Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or a Bachelor's degree with 8+ years of professional or military experience.
Preferred
  • PhD degree in a life science discipline such as Biochemistry, Genetics, Molecular Biology, or Microbiology, with 8-10 years of directly related commercial experience.
  • Ability to work effectively within multidisciplinary teams at the interface of life science and computer science.
  • Broad familiarity with different areas of the life sciences and their experimental approaches.
  • Hands-on experience in high-throughput research, including operation of liquid handling systems.
  • 2+ years of experience with data visualization tools such as AWS QuickSight, Tableau, or R Shiny.
  • Experience using AWS and related cloud-based tools in support of data pipelines and analytics.
  • Experience serving as a leader and mentor on a data science team, supporting the development of colleagues' technical and analytical skills.
Responsibilities
  • Execute existing laboratory workflows from experimental planning through data analysis, ensuring accuracy, reproducibility, and timely completion of work.
  • Recognize, document, and escalate protocol deviations to relevant stakeholders, and contribute to corrective and preventive actions.
  • Ensure laboratory equipment and instruments remain in good operating condition, identify malfunctions, and perform or coordinate troubleshooting as needed.
  • Maintain an up-to-date understanding of laboratory methods, protocols, and analytical techniques used in the lab.
  • Provide structured feedback on laboratory workflows and participate in developing solutions to process bottlenecks, throughput limitations, and data quality issues.
  • Work with a team of researchers to extend, refine, and interpret advanced analytical methodologies in the life sciences.
  • Facilitate effective interactions with internal and external collaborators to improve efficiency and implementation of cutting-edge analytical methods.
  • Adapt to unexpected schedule changes and respond to urgent or emergency situations in the laboratory environment as needed.
  • Extract, clean, and analyze complex datasets using data querying and scripting languages, and build statistical models to support scientific and business decisions.
  • Develop, implement, and maintain robust data pipelines that support laboratory workflows and analytical processes.
  • Apply statistical and machine learning models, such as multinomial logistic regression, to derive insights from experimental and operational data.
  • Create clear, insightful visualizations and reports using data visualization tools to communicate findings to technical and non-technical stakeholders.
  • Communicate results, methods, and recommendations clearly in both written and verbal form, tailoring the level of detail to the audience.
  • Act as a leader and mentor within the data science function, guiding colleagues on best practices in data extraction, analysis, modeling, and communication.
  • Ensure adherence to laboratory safety procedures, including proper operation of laboratory equipment and safe handling of chemical and biological hazards.
View full posting on CareerOneStop → ID: c817b8fb9e7f
Data Scientist III
Indeed · Seattle, WA
Mid-level Doctorate
2026-05-23
Responsibilities
  • As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
  • You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
  • Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
  • Translate data into actionable insights to guide product, marketing and business decisions.
  • Develop and maintain scalable, robust data pipelines and models for large-scale product data. Collaborate with engineering and product teams to integrate data science solutions into product workflows.
  • Mentor and support other data scientists, promoting knowledge sharing and best practices.
  • Contribute to the development of AI agents and skills, methodologies, and processes that improve the efficiency and impact of the data science team.
  • Communicate findings clearly through presentations, visualizations, and documentation for diverse audiences.
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
  • Expertise in A/B testing and experimentation is required
  • Solid foundation in data science methods and technologies.
  • Able to influence technical direction and contribute to long-term planning.
  • Able to work effectively with other teams and mentor colleagues.
  • Focused on delivering high-quality, impactful solutions that contribute to business goals.
  • Excellent written and verbal communication in English, effective with technical and business audiences.
View full posting on CareerOneStop → ID: 01370a76aa69
Principal Data Scientist
Microsoft Corporation · Redmond, WA
Senior Doctorate
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
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
Requirements
  • Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
  • 3+ years of experience in AI/ML algorithm development using core data science languages and frameworks (Python, PyTorch, etc.) and data analysis (NLP, time-series analysis, computer vision)
  • 3+ years of experience and a proven track record applying traditional ML and deep learning techniques (CNNs, RNNs, GANs) across real-world projects, including model tuning and performance validation in production environments
  • 3+ years of experience deploying and optimizing ML models using tools like Kubernetes, Docker, TensorRT/Trion, RAPIDs, Kubeflow, and MLflow
  • 3+ years of experience in leveraging cloud environments (AWS, Azure, or GCP) to deploy AI/ML workloads
  • Live within commuting distance to one of Deloitte's consulting offices
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available
Preferred
  • 2+ years of experience working in a client-facing, consulting environment
  • 2+ years of experience leading project/client engagement teams in the execution of complex AI data science solutions
  • 1+ year of experience with LLM/GenAI use cases and developing RAG solutions, tools, and services (i.e., LangChain, LangGraph, MCP, etc.)
  • 1+ year of experience with AWS Sagemaker or AWS ML Studio
  • The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $128,000 to $252,500.
  • You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
View full posting on CareerOneStop → ID: 786722d6ad58
Data Science Manager, Gen AI - SFL Scientific
Deloitte · Portland, OR
Manager Doctorate
2026-05-23
Requirements
  • Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
  • 6+ years of experience working in data science, data engineering, software engineering, or MLOps
  • 6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
  • 6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
  • 6+ years of experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms
  • 4+ years of experience managing teams and delivering complex and critical projects
  • Live within commuting distance to one of Deloitte's consulting offices
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available
Preferred
  • Experience with cloud deployment (AWS, Azure, GCP), such as building and scaling in AWS SageMaker or Azure ML Studio
  • Experience with developing and testing GenAI solutions
  • Experience in a client-facing role or internal AI product development role
  • Highly proficient written and verbal skills to support briefings, proposals, technical sprint plans, solution reports, progress updates, and executive presentations
  • The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.
  • You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
View full posting on CareerOneStop → ID: 51a9883c9b6b
Data Scientist III
Indeed · Portland, OR
Mid-level Doctorate
2026-05-23
Responsibilities
  • As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
  • You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
  • Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
  • Translate data into actionable insights to guide product, marketing and business decisions.
  • Develop and maintain scalable, robust data pipelines and models for large-scale product data. Collaborate with engineering and product teams to integrate data science solutions into product workflows.
  • Mentor and support other data scientists, promoting knowledge sharing and best practices.
  • Contribute to the development of AI agents and skills, methodologies, and processes that improve the efficiency and impact of the data science team.
  • Communicate findings clearly through presentations, visualizations, and documentation for diverse audiences.
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
  • Expertise in A/B testing and experimentation is required
  • Solid foundation in data science methods and technologies.
  • Able to influence technical direction and contribute to long-term planning.
  • Able to work effectively with other teams and mentor colleagues.
  • Focused on delivering high-quality, impactful solutions that contribute to business goals.
  • Excellent written and verbal communication in English, effective with technical and business audiences.
View full posting on CareerOneStop → ID: fb37eb36abff
Senior Data Scientist - SFL Scientific
Deloitte · Portland, OR
Senior Doctorate
2026-05-23
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 III
Indeed · Boise, ID
Mid-level Doctorate
2026-05-23
Responsibilities
  • As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
  • You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
  • Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
  • Translate data into actionable insights to guide product, marketing and business decisions.
  • Develop and maintain scalable, robust data pipelines and models for large-scale product data. Collaborate with engineering and product teams to integrate data science solutions into product workflows.
  • Mentor and support other data scientists, promoting knowledge sharing and best practices.
  • Contribute to the development of AI agents and skills, methodologies, and processes that improve the efficiency and impact of the data science team.
  • Communicate findings clearly through presentations, visualizations, and documentation for diverse audiences.
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
  • Expertise in A/B testing and experimentation is required
  • Solid foundation in data science methods and technologies.
  • Able to influence technical direction and contribute to long-term planning.
  • Able to work effectively with other teams and mentor colleagues.
  • Focused on delivering high-quality, impactful solutions that contribute to business goals.
  • Excellent written and verbal communication in English, effective with technical and business audiences.
View full posting on CareerOneStop → ID: cb8be40266ce
Data Scientist III
Indeed · Helena, MT
Mid-level Doctorate
2026-05-23
Responsibilities
  • As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI and machine learning to take on complex product, marketing and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization.
  • You will work closely with engineering and product or marketing teams to identify opportunities, evaluate initiatives, and develop models and analyses that inform data-driven strategies. You will also contribute to building best practices in data science and mentor others in the team, helping elevate the technical capabilities and impact of those around you.
  • Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions.
  • Translate data into actionable insights to guide product, marketing and business decisions.
  • Develop and maintain scalable, robust data pipelines and models for large-scale product data. Collaborate with engineering and product teams to integrate data science solutions into product workflows.
  • Mentor and support other data scientists, promoting knowledge sharing and best practices.
  • Contribute to the development of AI agents and skills, methodologies, and processes that improve the efficiency and impact of the data science team.
  • Communicate findings clearly through presentations, visualizations, and documentation for diverse audiences.
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
  • Expertise in A/B testing and experimentation is required
  • Solid foundation in data science methods and technologies.
  • Able to influence technical direction and contribute to long-term planning.
  • Able to work effectively with other teams and mentor colleagues.
  • Focused on delivering high-quality, impactful solutions that contribute to business goals.
  • Excellent written and verbal communication in English, effective with technical and business audiences.
View full posting on CareerOneStop → ID: 46eaf2e8109e
Senior Data Scientist, Special Projects
Amazon · Seattle, WA
Senior Doctorate
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
Data Scientist - Senior Manager- Consulting - Location OPEN
EY · Seattle, WA
Manager Doctorate
2026-05-21
Requirements
  • PhD preferred in Computer Science, Machine Learning, Computational Linguistics, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Master's with exceptional applied experience also considered.
  • 12+ years of applied data science / ML experience, with at least 3 years in a senior technical leadership role.
  • Demonstrable experience taking AI and ML systems from prototype to production - across multiple problem types (e.g., predictive modeling, NLP, retrieval / RAG, optimization, or agentic workflows).
  • Hands-on proficiency in Python and the modern ML/AI stack (PyTorch, Hugging Face, scikit-learn, and at least one of LangChain / LangGraph or an equivalent agent / LLM framework).
  • Practical experience with at least one major cloud AI platform (Vertex AI, Bedrock, Azure AI Foundry, Databricks Mosaic AI) and one vector / retrieval stack.
  • Experience designing evaluation frameworks for AI systems - beyond standard benchmarks - including evaluation for foundation-model-based or agentic workflows.
  • Experience operating in a client-facing or cross-functional environment, translating business problems into rigorous data-science programs.
  • *Ideally, you will also have
  • Published research or open-source contributions in AI / ML agentic systems, retrieval, memory and grounding, knowledge graphs, foundation models, optimization, or related areas.
  • Experience with knowledge graphs, ontologies, and neuro-symbolic approaches to grounding and reasoning.
  • Experience building or contributing to a cognitive harness, agent operating system, or agent runtime - internal or open source.
  • Experience with continual learning, online evaluation, drift detection, and model / memory monitoring in production.
  • Familiarity with regulated-industry constraints (SOX, HIPAA, GDPR) and how AI design interacts with audit, retention, and explainability.
  • Prior consulting, product, or hyperscaler experience - comfortable in a fast, ambiguous environment with senior stakeholders.
  • *What we look fo
  • We are looking for a data-science leader who is genuinely excited about hard technical problems and who is as comfortable in a research paper as in a production codebase. You should be the kind of person who treats AI systems as engineered products designed, evaluated, and operated with rigor and who wants to lead a team that ships to Fortune 500 clients across multiple industries.
Responsibilities
  • As a Senior Manager, Data Scientist, you will be a hands-on technical leader who shapes the data-science agenda across multiple workstreams. You will own technical direction, experimentation, and the path from prototype to production for the problems you take on. You will be expected to build, not just design and to lift the bar of the team around you.
  • Lead data-science strategy and execution across multiple AI workstreams including agentic AI, the cognitive harness, memory and grounding, foundation-model applications, machine learning, optimization, and applied analytics.
  • Drive the applied-research and experimentation agenda long-context vs. retrieval trade-offs, hybrid search, reranking, evaluation design, model selection, fine-tuning, and emerging techniques as the field evolves.
  • Design and contribute to the build of core platform components including elements of EY's cognitive harness (memory services, retrieval pipelines, grounding layers, evaluation harnesses) and other reusable AI capabilities.
  • Establish evaluation and quality frameworks for AI systems retrieval and grounding fidelity, hallucination rate, model accuracy, latency, cost, fairness, and continuous evaluation in production.
  • Lead and mentor data scientists and ML engineers set the technical bar, run design reviews, and grow rigor in experimentation, model selection, and production readiness.
  • Partner with sector and functional teams (Finance, Risk, Tax, Supply Chain, HR, Operations) to translate business problems into rigorous, deliverable data-science programs.
  • Engage with clients on complex AI problems shape the technical approach, defend it in front of senior stakeholders, and own delivery quality.
  • Stay abreast of AI technology trends and provide directional guidance and recommendations around models, frameworks, tools, and patterns that fit our clients' existing ecosystems.
  • Apply combined business and technical knowledge to develop and execute target architectures that enable implementation, monitoring, and ongoing improvement of AI at scale.
  • *Skills and attributes for success
  • This role will work to deliver tech at speed, innovate at scale, and put humans at the center. You will provide technical guidance and share knowledge with team members with diverse skills and backgrounds. You will consistently deliver quality client services, focusing on more complex, judgmental, and specialized issues surrounding modern AI, foundation models, and emerging technology. You will demonstrate deep technical capabilities and professional knowledge, and you will lead through making.
  • Strong, hands-on data scientist who codes comfortable building and shipping models, pipelines, services, and experimental frameworks, not just specifying them.
  • Deep technical breadth across modern AI foundation models and prompting, retrieval and grounding, embeddings and fine-tuning, classical ML, optimization, and experimentation rigor.
  • Working knowledge of agentic systems and cognitive harness / agent-runtime architectures - memory, tools, policies, evaluation, observability, cost and the trade-offs between them.
  • Familiarity with at least one major agent SDK (Google ADK, AWS Bedrock AgentCore, LangGraph, AutoGen, OpenAI Agents SDK) and the ability to compare them critically.
  • Experience designing and operating production AI systems on cloud platforms (GCP, AWS, Azure, Databricks) including responsible-AI guardrails, monitoring, and continuous evaluation.
  • Track record of leading data-science teams across multiple projects setting technical strategy, mentoring, and raising the bar on rigor and delivery quality.
  • Excellent communication skills able to explain complex AI concepts to executive clients, and able to defend technical choices in front of architects, engineers, and researchers.
  • Comfortable moving between problem spaces - equally credible designing a memory architecture, evaluating a forecasting model, or shaping a new agentic workflow.
View full posting on CareerOneStop → ID: d4ce7ce958d6
Data Scientist - Senior Manager- Consulting - Location OPEN
EY · Olympia, WA
Manager Doctorate
2026-05-21
Requirements
  • PhD preferred in Computer Science, Machine Learning, Computational Linguistics, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Master's with exceptional applied experience also considered.
  • 12+ years of applied data science / ML experience, with at least 3 years in a senior technical leadership role.
  • Demonstrable experience taking AI and ML systems from prototype to production - across multiple problem types (e.g., predictive modeling, NLP, retrieval / RAG, optimization, or agentic workflows).
  • Hands-on proficiency in Python and the modern ML/AI stack (PyTorch, Hugging Face, scikit-learn, and at least one of LangChain / LangGraph or an equivalent agent / LLM framework).
  • Practical experience with at least one major cloud AI platform (Vertex AI, Bedrock, Azure AI Foundry, Databricks Mosaic AI) and one vector / retrieval stack.
  • Experience designing evaluation frameworks for AI systems - beyond standard benchmarks - including evaluation for foundation-model-based or agentic workflows.
  • Experience operating in a client-facing or cross-functional environment, translating business problems into rigorous data-science programs.
  • *Ideally, you will also have
  • Published research or open-source contributions in AI / ML agentic systems, retrieval, memory and grounding, knowledge graphs, foundation models, optimization, or related areas.
  • Experience with knowledge graphs, ontologies, and neuro-symbolic approaches to grounding and reasoning.
  • Experience building or contributing to a cognitive harness, agent operating system, or agent runtime - internal or open source.
  • Experience with continual learning, online evaluation, drift detection, and model / memory monitoring in production.
  • Familiarity with regulated-industry constraints (SOX, HIPAA, GDPR) and how AI design interacts with audit, retention, and explainability.
  • Prior consulting, product, or hyperscaler experience - comfortable in a fast, ambiguous environment with senior stakeholders.
  • *What we look fo
  • We are looking for a data-science leader who is genuinely excited about hard technical problems and who is as comfortable in a research paper as in a production codebase. You should be the kind of person who treats AI systems as engineered products designed, evaluated, and operated with rigor and who wants to lead a team that ships to Fortune 500 clients across multiple industries.
Responsibilities
  • As a Senior Manager, Data Scientist, you will be a hands-on technical leader who shapes the data-science agenda across multiple workstreams. You will own technical direction, experimentation, and the path from prototype to production for the problems you take on. You will be expected to build, not just design and to lift the bar of the team around you.
  • Lead data-science strategy and execution across multiple AI workstreams including agentic AI, the cognitive harness, memory and grounding, foundation-model applications, machine learning, optimization, and applied analytics.
  • Drive the applied-research and experimentation agenda long-context vs. retrieval trade-offs, hybrid search, reranking, evaluation design, model selection, fine-tuning, and emerging techniques as the field evolves.
  • Design and contribute to the build of core platform components including elements of EY's cognitive harness (memory services, retrieval pipelines, grounding layers, evaluation harnesses) and other reusable AI capabilities.
  • Establish evaluation and quality frameworks for AI systems retrieval and grounding fidelity, hallucination rate, model accuracy, latency, cost, fairness, and continuous evaluation in production.
  • Lead and mentor data scientists and ML engineers set the technical bar, run design reviews, and grow rigor in experimentation, model selection, and production readiness.
  • Partner with sector and functional teams (Finance, Risk, Tax, Supply Chain, HR, Operations) to translate business problems into rigorous, deliverable data-science programs.
  • Engage with clients on complex AI problems shape the technical approach, defend it in front of senior stakeholders, and own delivery quality.
  • Stay abreast of AI technology trends and provide directional guidance and recommendations around models, frameworks, tools, and patterns that fit our clients' existing ecosystems.
  • Apply combined business and technical knowledge to develop and execute target architectures that enable implementation, monitoring, and ongoing improvement of AI at scale.
  • *Skills and attributes for success
  • This role will work to deliver tech at speed, innovate at scale, and put humans at the center. You will provide technical guidance and share knowledge with team members with diverse skills and backgrounds. You will consistently deliver quality client services, focusing on more complex, judgmental, and specialized issues surrounding modern AI, foundation models, and emerging technology. You will demonstrate deep technical capabilities and professional knowledge, and you will lead through making.
  • Strong, hands-on data scientist who codes comfortable building and shipping models, pipelines, services, and experimental frameworks, not just specifying them.
  • Deep technical breadth across modern AI foundation models and prompting, retrieval and grounding, embeddings and fine-tuning, classical ML, optimization, and experimentation rigor.
  • Working knowledge of agentic systems and cognitive harness / agent-runtime architectures - memory, tools, policies, evaluation, observability, cost and the trade-offs between them.
  • Familiarity with at least one major agent SDK (Google ADK, AWS Bedrock AgentCore, LangGraph, AutoGen, OpenAI Agents SDK) and the ability to compare them critically.
  • Experience designing and operating production AI systems on cloud platforms (GCP, AWS, Azure, Databricks) including responsible-AI guardrails, monitoring, and continuous evaluation.
  • Track record of leading data-science teams across multiple projects setting technical strategy, mentoring, and raising the bar on rigor and delivery quality.
  • Excellent communication skills able to explain complex AI concepts to executive clients, and able to defend technical choices in front of architects, engineers, and researchers.
  • Comfortable moving between problem spaces - equally credible designing a memory architecture, evaluating a forecasting model, or shaping a new agentic workflow.
View full posting on CareerOneStop → ID: 4f65551cb8e5
Data Scientist, Manufacturing Analytics
Ford Motor Company · Olympia, WA
Mid-level Doctorate
2026-05-21
Responsibilities
  • Accelerate the application of value-added analytics and machine learning into the portfolio of products for Manufacturing Analytics.
  • Drive analytic excellence into product teams by collaborating with Data Scientists, Data Engineers and Software Engineers in analytic and machine learning methods.
  • Work closely with the Product Manager and Product Owner to translate Business Value needs into analytic deliverables and, where appropriate, software products for delivery by product teams.
  • Work hands-on with the team and other partners to deliver solutions that meet our customer's requirements and needs.
  • Act as a consultant to the business vs. an order taker.
  • Balance "doing it right" with "speed to delivery" by identifying and mitigating risk, generating options, educating business and other decision makers, and taking on justified technical debt.
  • *You'll have...
  • Bachelor's degree in a quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics OR Computer Science
  • 2+ year experience hands-on experience with mathematical programming, machine learning, artificial intelligence, optimization/simulation techniques, or statistical analysis
  • 1+ year of experience delivering analytics solutions
  • 1+ year experience with Agile team methodology
  • Demonstrated technical skills in data analytics, AI/ML, operations research, and/or optimization
  • *Even better, you may have...
  • Master's degree or PhD preferred in quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics, Computer Science, or related field
  • Knowledge and experience working with OGC and related teams/activities (e.g., Compliance, Litigation and Regulatory)
  • Proven experience with developing data products/solutions to support analytic applications in Ford's data ecosystem
  • Experience with Product Driven Operating Model or Agile Product Development Process
  • Proven proficiency in developing and deploying analytic models, working in a team environment, supporting customers and/or end users
  • Comfortable working in an environment where problems are not always well-defined
  • Strong interpersonal and leadership skills, with ability to communicate complex topics to leaders and peers in a simple and clear manne
  • Well-organized, independent, and ready to work with minimal supervision
  • Inquisitive, proactive, and interested in learning new tools and techniques
  • Demonstrated hands on experience with deploying data products and/or analytic models in Ford's on-prem and/or Google Cloud Platform
  • Demonstrated experience to translate real-world business problems into analytical formulations and interpreting analytics results with non-analytics business partners
  • Working knowledge of Manufacturing IT legacy systems such as FIS, Maximo, QLS, etc.
  • Thorough understanding of the 'Common Data Model' standard published by Manufacturing
  • Understanding of the IIoT Platform architecture including MQTT
  • You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
  • As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder...or all of the above? No matter what you choose, we offer a work life that works for you, including:
  • Immediate medical, dental, vision and prescription drug coverage
  • Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
  • Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
  • Vehicle discount program for employees and family members and management leases
  • Tuition assistance
  • Established and active employee resource groups
  • Paid time off for individual and team community service
  • A generous schedule of paid holidays, including the week between Christmas and New Year's Day
  • Paid time off and the option to purchase additional vacation time.
  • This position is a salary grade 5 - salary grade 8 and ranges from $68,300-$192,900.
View full posting on CareerOneStop → ID: aff447194327
Data Scientist - Senior Manager- Consulting - Location OPEN
EY · Portland, OR
Manager Doctorate
2026-05-21
Requirements
  • PhD preferred in Computer Science, Machine Learning, Computational Linguistics, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Master's with exceptional applied experience also considered.
  • 12+ years of applied data science / ML experience, with at least 3 years in a senior technical leadership role.
  • Demonstrable experience taking AI and ML systems from prototype to production - across multiple problem types (e.g., predictive modeling, NLP, retrieval / RAG, optimization, or agentic workflows).
  • Hands-on proficiency in Python and the modern ML/AI stack (PyTorch, Hugging Face, scikit-learn, and at least one of LangChain / LangGraph or an equivalent agent / LLM framework).
  • Practical experience with at least one major cloud AI platform (Vertex AI, Bedrock, Azure AI Foundry, Databricks Mosaic AI) and one vector / retrieval stack.
  • Experience designing evaluation frameworks for AI systems - beyond standard benchmarks - including evaluation for foundation-model-based or agentic workflows.
  • Experience operating in a client-facing or cross-functional environment, translating business problems into rigorous data-science programs.
  • *Ideally, you will also have
  • Published research or open-source contributions in AI / ML agentic systems, retrieval, memory and grounding, knowledge graphs, foundation models, optimization, or related areas.
  • Experience with knowledge graphs, ontologies, and neuro-symbolic approaches to grounding and reasoning.
  • Experience building or contributing to a cognitive harness, agent operating system, or agent runtime - internal or open source.
  • Experience with continual learning, online evaluation, drift detection, and model / memory monitoring in production.
  • Familiarity with regulated-industry constraints (SOX, HIPAA, GDPR) and how AI design interacts with audit, retention, and explainability.
  • Prior consulting, product, or hyperscaler experience - comfortable in a fast, ambiguous environment with senior stakeholders.
  • *What we look fo
  • We are looking for a data-science leader who is genuinely excited about hard technical problems and who is as comfortable in a research paper as in a production codebase. You should be the kind of person who treats AI systems as engineered products designed, evaluated, and operated with rigor and who wants to lead a team that ships to Fortune 500 clients across multiple industries.
Responsibilities
  • As a Senior Manager, Data Scientist, you will be a hands-on technical leader who shapes the data-science agenda across multiple workstreams. You will own technical direction, experimentation, and the path from prototype to production for the problems you take on. You will be expected to build, not just design and to lift the bar of the team around you.
  • Lead data-science strategy and execution across multiple AI workstreams including agentic AI, the cognitive harness, memory and grounding, foundation-model applications, machine learning, optimization, and applied analytics.
  • Drive the applied-research and experimentation agenda long-context vs. retrieval trade-offs, hybrid search, reranking, evaluation design, model selection, fine-tuning, and emerging techniques as the field evolves.
  • Design and contribute to the build of core platform components including elements of EY's cognitive harness (memory services, retrieval pipelines, grounding layers, evaluation harnesses) and other reusable AI capabilities.
  • Establish evaluation and quality frameworks for AI systems retrieval and grounding fidelity, hallucination rate, model accuracy, latency, cost, fairness, and continuous evaluation in production.
  • Lead and mentor data scientists and ML engineers set the technical bar, run design reviews, and grow rigor in experimentation, model selection, and production readiness.
  • Partner with sector and functional teams (Finance, Risk, Tax, Supply Chain, HR, Operations) to translate business problems into rigorous, deliverable data-science programs.
  • Engage with clients on complex AI problems shape the technical approach, defend it in front of senior stakeholders, and own delivery quality.
  • Stay abreast of AI technology trends and provide directional guidance and recommendations around models, frameworks, tools, and patterns that fit our clients' existing ecosystems.
  • Apply combined business and technical knowledge to develop and execute target architectures that enable implementation, monitoring, and ongoing improvement of AI at scale.
  • *Skills and attributes for success
  • This role will work to deliver tech at speed, innovate at scale, and put humans at the center. You will provide technical guidance and share knowledge with team members with diverse skills and backgrounds. You will consistently deliver quality client services, focusing on more complex, judgmental, and specialized issues surrounding modern AI, foundation models, and emerging technology. You will demonstrate deep technical capabilities and professional knowledge, and you will lead through making.
  • Strong, hands-on data scientist who codes comfortable building and shipping models, pipelines, services, and experimental frameworks, not just specifying them.
  • Deep technical breadth across modern AI foundation models and prompting, retrieval and grounding, embeddings and fine-tuning, classical ML, optimization, and experimentation rigor.
  • Working knowledge of agentic systems and cognitive harness / agent-runtime architectures - memory, tools, policies, evaluation, observability, cost and the trade-offs between them.
  • Familiarity with at least one major agent SDK (Google ADK, AWS Bedrock AgentCore, LangGraph, AutoGen, OpenAI Agents SDK) and the ability to compare them critically.
  • Experience designing and operating production AI systems on cloud platforms (GCP, AWS, Azure, Databricks) including responsible-AI guardrails, monitoring, and continuous evaluation.
  • Track record of leading data-science teams across multiple projects setting technical strategy, mentoring, and raising the bar on rigor and delivery quality.
  • Excellent communication skills able to explain complex AI concepts to executive clients, and able to defend technical choices in front of architects, engineers, and researchers.
  • Comfortable moving between problem spaces - equally credible designing a memory architecture, evaluating a forecasting model, or shaping a new agentic workflow.
View full posting on CareerOneStop → ID: 06cb3337d70e
Data Scientist - Senior Manager- Consulting - Location OPEN
EY · Salem, OR
Manager Doctorate
2026-05-21
Requirements
  • PhD preferred in Computer Science, Machine Learning, Computational Linguistics, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Master's with exceptional applied experience also considered.
  • 12+ years of applied data science / ML experience, with at least 3 years in a senior technical leadership role.
  • Demonstrable experience taking AI and ML systems from prototype to production - across multiple problem types (e.g., predictive modeling, NLP, retrieval / RAG, optimization, or agentic workflows).
  • Hands-on proficiency in Python and the modern ML/AI stack (PyTorch, Hugging Face, scikit-learn, and at least one of LangChain / LangGraph or an equivalent agent / LLM framework).
  • Practical experience with at least one major cloud AI platform (Vertex AI, Bedrock, Azure AI Foundry, Databricks Mosaic AI) and one vector / retrieval stack.
  • Experience designing evaluation frameworks for AI systems - beyond standard benchmarks - including evaluation for foundation-model-based or agentic workflows.
  • Experience operating in a client-facing or cross-functional environment, translating business problems into rigorous data-science programs.
  • *Ideally, you will also have
  • Published research or open-source contributions in AI / ML agentic systems, retrieval, memory and grounding, knowledge graphs, foundation models, optimization, or related areas.
  • Experience with knowledge graphs, ontologies, and neuro-symbolic approaches to grounding and reasoning.
  • Experience building or contributing to a cognitive harness, agent operating system, or agent runtime - internal or open source.
  • Experience with continual learning, online evaluation, drift detection, and model / memory monitoring in production.
  • Familiarity with regulated-industry constraints (SOX, HIPAA, GDPR) and how AI design interacts with audit, retention, and explainability.
  • Prior consulting, product, or hyperscaler experience - comfortable in a fast, ambiguous environment with senior stakeholders.
  • *What we look fo
  • We are looking for a data-science leader who is genuinely excited about hard technical problems and who is as comfortable in a research paper as in a production codebase. You should be the kind of person who treats AI systems as engineered products designed, evaluated, and operated with rigor and who wants to lead a team that ships to Fortune 500 clients across multiple industries.
Responsibilities
  • As a Senior Manager, Data Scientist, you will be a hands-on technical leader who shapes the data-science agenda across multiple workstreams. You will own technical direction, experimentation, and the path from prototype to production for the problems you take on. You will be expected to build, not just design and to lift the bar of the team around you.
  • Lead data-science strategy and execution across multiple AI workstreams including agentic AI, the cognitive harness, memory and grounding, foundation-model applications, machine learning, optimization, and applied analytics.
  • Drive the applied-research and experimentation agenda long-context vs. retrieval trade-offs, hybrid search, reranking, evaluation design, model selection, fine-tuning, and emerging techniques as the field evolves.
  • Design and contribute to the build of core platform components including elements of EY's cognitive harness (memory services, retrieval pipelines, grounding layers, evaluation harnesses) and other reusable AI capabilities.
  • Establish evaluation and quality frameworks for AI systems retrieval and grounding fidelity, hallucination rate, model accuracy, latency, cost, fairness, and continuous evaluation in production.
  • Lead and mentor data scientists and ML engineers set the technical bar, run design reviews, and grow rigor in experimentation, model selection, and production readiness.
  • Partner with sector and functional teams (Finance, Risk, Tax, Supply Chain, HR, Operations) to translate business problems into rigorous, deliverable data-science programs.
  • Engage with clients on complex AI problems shape the technical approach, defend it in front of senior stakeholders, and own delivery quality.
  • Stay abreast of AI technology trends and provide directional guidance and recommendations around models, frameworks, tools, and patterns that fit our clients' existing ecosystems.
  • Apply combined business and technical knowledge to develop and execute target architectures that enable implementation, monitoring, and ongoing improvement of AI at scale.
  • *Skills and attributes for success
  • This role will work to deliver tech at speed, innovate at scale, and put humans at the center. You will provide technical guidance and share knowledge with team members with diverse skills and backgrounds. You will consistently deliver quality client services, focusing on more complex, judgmental, and specialized issues surrounding modern AI, foundation models, and emerging technology. You will demonstrate deep technical capabilities and professional knowledge, and you will lead through making.
  • Strong, hands-on data scientist who codes comfortable building and shipping models, pipelines, services, and experimental frameworks, not just specifying them.
  • Deep technical breadth across modern AI foundation models and prompting, retrieval and grounding, embeddings and fine-tuning, classical ML, optimization, and experimentation rigor.
  • Working knowledge of agentic systems and cognitive harness / agent-runtime architectures - memory, tools, policies, evaluation, observability, cost and the trade-offs between them.
  • Familiarity with at least one major agent SDK (Google ADK, AWS Bedrock AgentCore, LangGraph, AutoGen, OpenAI Agents SDK) and the ability to compare them critically.
  • Experience designing and operating production AI systems on cloud platforms (GCP, AWS, Azure, Databricks) including responsible-AI guardrails, monitoring, and continuous evaluation.
  • Track record of leading data-science teams across multiple projects setting technical strategy, mentoring, and raising the bar on rigor and delivery quality.
  • Excellent communication skills able to explain complex AI concepts to executive clients, and able to defend technical choices in front of architects, engineers, and researchers.
  • Comfortable moving between problem spaces - equally credible designing a memory architecture, evaluating a forecasting model, or shaping a new agentic workflow.
View full posting on CareerOneStop → ID: cd7c9bd89325
Data Scientist, Manufacturing Analytics
Ford Motor Company · Salem, OR
Mid-level Doctorate
2026-05-21
Responsibilities
  • Accelerate the application of value-added analytics and machine learning into the portfolio of products for Manufacturing Analytics.
  • Drive analytic excellence into product teams by collaborating with Data Scientists, Data Engineers and Software Engineers in analytic and machine learning methods.
  • Work closely with the Product Manager and Product Owner to translate Business Value needs into analytic deliverables and, where appropriate, software products for delivery by product teams.
  • Work hands-on with the team and other partners to deliver solutions that meet our customer's requirements and needs.
  • Act as a consultant to the business vs. an order taker.
  • Balance "doing it right" with "speed to delivery" by identifying and mitigating risk, generating options, educating business and other decision makers, and taking on justified technical debt.
  • *You'll have...
  • Bachelor's degree in a quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics OR Computer Science
  • 2+ year experience hands-on experience with mathematical programming, machine learning, artificial intelligence, optimization/simulation techniques, or statistical analysis
  • 1+ year of experience delivering analytics solutions
  • 1+ year experience with Agile team methodology
  • Demonstrated technical skills in data analytics, AI/ML, operations research, and/or optimization
  • *Even better, you may have...
  • Master's degree or PhD preferred in quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics, Computer Science, or related field
  • Knowledge and experience working with OGC and related teams/activities (e.g., Compliance, Litigation and Regulatory)
  • Proven experience with developing data products/solutions to support analytic applications in Ford's data ecosystem
  • Experience with Product Driven Operating Model or Agile Product Development Process
  • Proven proficiency in developing and deploying analytic models, working in a team environment, supporting customers and/or end users
  • Comfortable working in an environment where problems are not always well-defined
  • Strong interpersonal and leadership skills, with ability to communicate complex topics to leaders and peers in a simple and clear manne
  • Well-organized, independent, and ready to work with minimal supervision
  • Inquisitive, proactive, and interested in learning new tools and techniques
  • Demonstrated hands on experience with deploying data products and/or analytic models in Ford's on-prem and/or Google Cloud Platform
  • Demonstrated experience to translate real-world business problems into analytical formulations and interpreting analytics results with non-analytics business partners
  • Working knowledge of Manufacturing IT legacy systems such as FIS, Maximo, QLS, etc.
  • Thorough understanding of the 'Common Data Model' standard published by Manufacturing
  • Understanding of the IIoT Platform architecture including MQTT
  • You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
  • As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder...or all of the above? No matter what you choose, we offer a work life that works for you, including:
  • Immediate medical, dental, vision and prescription drug coverage
  • Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
  • Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
  • Vehicle discount program for employees and family members and management leases
  • Tuition assistance
  • Established and active employee resource groups
  • Paid time off for individual and team community service
  • A generous schedule of paid holidays, including the week between Christmas and New Year's Day
  • Paid time off and the option to purchase additional vacation time.
  • This position is a salary grade 5 - salary grade 8 and ranges from $68,300-$192,900.
View full posting on CareerOneStop → ID: bfc28dd922c9
Data Scientist , AMXL Worldwide Science
Amazon · Bellevue, WA
Mid-level Doctorate
2026-05-20
Requirements
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • 1+ years of guiding and coaching a group of researchers experience
  • 1+ years of working with or evaluating AI systems experience
  • 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
  • Experience applying theoretical models in an applied environment
Preferred
  • Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in Python, Perl, or another scripting language
  • Experience in a ML or data scientist role with a large technology company
  • Experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience working on multi-team, cross-disciplinary projects
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication
Responsibilities
  • Apply machine learning, statistical modeling, time series analysis, and operations research techniques to build solutions for delivery routing, capacity planning, demand forecasting, workforce scheduling, and network optimization
  • Analyze large-scale historical and real-time operational data to surface efficiency patterns, bottlenecks, and emerging trends across the AMXL network
  • Develop, validate, and deploy models that improve cost-to-serve and customer experience
  • Partner with cross-functional teams to implement data-driven strategies and measure impact
  • Build scalable, automated pipelines for data ingestion, feature engineering, model training, and validation
  • Monitor deployed model performance and communicate results through clear reporting on key operational and business metrics
View full posting on CareerOneStop → ID: 22260e66a090
Senior Applied Data Scientist
Eliassen Group · Olympia, WA
Senior Doctorate
2026-05-20
Requirements
  • Strong applied data science background, including optimization, forecasting, or prescriptive analytics in a business environment
  • Proficient Python development skills with experience supporting or deploying models in production systems
  • Strong SQL expertise, including complex query writing and performance tuning
Education
  • PhD in a quantitative field (e.g., Data Science, Mathematics, Statistics, Computer Science, Industrial Engineering, Operations Research) with 2+ years of applied industry experience OR
  • Master's degree in a quantitative field with 5+ years of applied data science experience OR
  • Bachelor's degree in a quantitative or technical field with 7+ years of applied data science experience
  • *_Recruitment Transparency Notice_
  • *_Eliassen Group values transparency in our recruitment practices. Please be advised that Eliassen Group utilizes artificial intelligence (AI) tools as part of its initial application screening_ _and hiring_ _process. You may receive email and SMS notifications from the Eliassen Virtual Recruiting Team (_ _noreply@eliassen.com_ _, 781-808-2924) inviting you to complete a brief voice screening as part of your application process. These tools assist our hiring teams in different ways, including but not limited to, assistance in reviewing application materials to help identify candidates whose qualifications most closely match the requirements of the position. All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring decisions are made. The use of AI in our process is intended to support fairness, efficiency, and consistency, and Eliassen Group takes measures to prevent bias or discrimination in connection with its hiring practices. By proceeding, you acknowledge, agree, and consent to Eliassen Group's use of these tools, including AI tools, as part of the application and hiring process._
  • _Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range._
Responsibilities
  • Design, develop, and own applied data science and optimization models supporting a pricing engine for products and services
  • Apply prescriptive analytics, forecasting, and operations research techniques to pricing, discounting, and value optimization problems
  • Translate business requirements into mathematical formulations and data-driven solutions with measurable business impact
  • Operationalize and support models using production-quality Python development to deploy solutions into production environments
  • Write, optimize, and tune complex SQL queries to support large-scale data access, feature generation, and model validation
View full posting on CareerOneStop → ID: 033f9d0d7814
Data Scientist III
Chewy Inc. · Bellevue, WA
Mid-level Doctorate
2026-05-20
Requirements
  • At least one data science subject area (e.g., casual inference, LLM's, forecasting, etc.);
  • Managing the entire data science lifecycle including data prep, exploratory data analysis, modeling, interface with cross functional stakeholders (such as engineering, business, etc.), deploying models to production;
  • Amazon Web Services tools such as Snowflake;
  • R, PySpark, Spark, Keras, TensorFlow, Docker, Git version control;
  • Object-oriented programming with Python;
  • Data visualization tools and packages (Tableau or similar); and
View full posting on CareerOneStop → ID: 8464227eb95e
Data Scientist III
Chewy Inc. · Bellevue, WA
Mid-level Doctorate
2026-05-20
Requirements
  • At least one data science subject area (e.g., casual inference, NLP, forecasting, etc.);
  • R, PySpark, Spark, Scala, Java, PyTorch, TensorFlow, Docker;
  • Object-oriented programming with Python; and
  • Data visualization tools and packages (Tableau or similar).
  • Managing the entire data science lifecycle including data prep, exploratory data analysis, modeling, interface with engineering;
  • Amazon Web Services tools such as Redshift, Snowflake, SageMaker or other similar platforms; and
View full posting on CareerOneStop → ID: a50291e8d3d9
Senior Applied Data Scientist
Eliassen Group · Boise, ID
Senior Doctorate
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
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
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 Machine Learning Engineer - Earner Incentive
Uber · Seattle, WA
Senior Doctorate
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
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
AI and Machine Learning Assistant Professor/Professional Pra
UTAH STATE UNIVERSITY · Logan, UT
Mid-level Doctorate
2026-05-18
Requirements
  • An earned doctorate degree in Electrical Engineering, Computer Engineering, Computer Science, Mathematics, Statistics, or a closely related discipline.
  • An ability to conduct and disseminate research that applies AI/ML to problems in the electrical engineering domain.
  • An ability to develop courses in AI/ML and effectively teach undergraduate and graduate level courses in AI/ML and the candidate's specific area of research emphasis in accordance with departmental needs.
  • An ability to apply for and secure ongoing external funding.
  • An earned MS degree in Electrical Engineering, Computer Engineering, Computer Science, Mathematics, Statistics, or equivalent work experience.
  • Strong industrial, commercial, consulting, or research experience in AI/ML systems.
  • An... For full info follow application link.
Preferred
  • Preference will be given to candidates with experience building and deploying AI/ML systems.
Responsibilities
  • Successful candidates for the tenure-track position will be expected to develop an externally funded research program that includes peer-reviewed publications and graduate student mentorship. Both tenure-track and professional practice positions are expected to effectively teach undergraduate and graduate courses, actively participate in assigned department and university duties, and serve their professional society. Ideal candidates will have an interest in developing new courses and degree programs in AI/ML and its applications to engineering.
View full posting on CareerOneStop → ID: a313763fc548
Technical Program Manager III, Machine Learning, Google Cloud
Google · Kirkland, WA
Manager Doctorate
2026-05-16
Requirements
  • Bachelor's degree in a relevant field, or equivalent practical experience.
  • 5 years of experience in program management.
  • Experience working with data structures or machine learning algorithms.
Preferred
  • Master's degree, PhD, or equivalent experience in Engineering, Computer Science, or other technical related field.
  • 5 years of experience managing cross-functional or cross-team projects.
  • 3 years of experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, or deep learning.
Responsibilities
  • A problem isn't truly solved until it's solved for all. That's why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you'll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You'll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.
  • Using your extensive technical and leadership expertise, you'll manage projects of various size and scope, identifying future opportunities, improving processes and driving the technical directions of your programs.
  • Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
  • The US base salary range for this full-time position is $163,000-$237,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
  • Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
  • Provide software development and project management, coordination, and inter/intra team communications to deliver outstanding program outcomes.
  • Work closely with Software Engineers, QA, Product Managers and other engineering teams to get high-quality products and features through the software project lifecycle (build, test and release on time).
  • Manage project schedules, identify possible issues and clearly communicate them to project stakeholders.
  • Lead several technical programs for Google Cloud, setting priorities for products and engineering, leading teams to take products to market, assuring success metrics are informing future efforts, and quickly fine tuning the program as needed.
  • Exercise knowledge of data structures or algorithms that improve software performance over time. Build, maintain and enhance business, operational, and management dashboards
  • Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
View full posting on CareerOneStop → ID: 87cede07c68e
Director, Data Science
Norstella · Boise, ID
Director Doctorate
2026-05-15
Requirements
  • 10+ years of experience developing and deploying AI/ML applications and delivering data-driven solutions at scale
  • Demonstrated experience leading and managing data science teams, including hiring, performance management, and talent development
  • Proven track record of building and scaling high-performing teams - including designing leveling frameworks, mentorship programs, and succession planning
  • Deep hands-on expertise in Generative AI, Large Language Models (LLMs), Agentic AI systems, and advanced NLP/Deep Learning techniques
  • Practical experience with LLM application design: prompt engineering, retrieval-augmented generation (RAG), model fine-tuning, tool use, and multi-agent orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen)
  • Graduate degree (Master's or PhD) in Computer Science, Engineering, Statistics, or a related quantitative discipline, or equivalent professional experience
  • Strong command of Python and core data science libraries (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow)
  • Deep understanding of CS fundamentals, computational complexity, and algorithm design
  • Experience architecting and delivering large-scale distributed systems in an agile environment, including rapid prototyping and iterative development
  • Excellent communication and stakeholder management skills - able to translate complex technical concepts for executive and non-technical audiences
Preferred
  • PhD in Computer Science with an AI/ML research focus and publications in top-tier venues
  • Experience in the healthcare or life sciences domain; familiarity with applying AI to pharmaceutical or market access data
  • Hands-on experience with AWS ML infrastructure: SageMaker, Lambda, S3, Snowflake, and related services
  • Experience with knowledge graphs, structured reasoning, and hybrid retrieval architectures
  • Prior experience operating at Director level or equivalent in a fast-paced, data-driven organization
Responsibilities
  • As Director of Data Science at Norstella, you will set the strategic vision for our data science capabilities and lead a high-performing team of data scientists and engineers. You will be a technical authority and a people-first leader - building talent, shaping culture, and delivering AI-powered solutions that have a direct impact on patient access to life-saving therapies.
  • Define and own the data science strategy, aligning closely with product, engineering, and executive leadership to drive roadmap prioritization
  • Lead, mentor, and grow a team of data scientists and ML engineers - fostering a culture of excellence, curiosity, and continuous learning
  • Build and develop talent: recruit top-tier data science professionals, design career development frameworks, and create pathways for growth at all levels
  • Champion the adoption of GenAI, Agentic AI, and LLM-powered architectures across the organization - defining reference frameworks for tool use, code interpretation, retrieval-augmented generation (RAG), and multi-agent workflows
  • Collaborate with product leadership to identify, elaborate, and prioritize high-impact projects
  • Oversee the delivery of AI-enabled microservices in collaboration with content and product engineering teams
  • Define and evolve engineering standards, best practices, and architectural patterns for scalable, production-grade AI systems
  • Stay at the cutting edge of AI/ML research; deliver regular presentations to internal stakeholders on emerging trends and their strategic implications
  • Partner cross-functionally to ensure data science solutions are operationalized effectively and drive measurable business value
  • All other duties, as assigned.
View full posting on CareerOneStop → ID: 6593366915af
Director, Data Science
Norstella · Salem, OR
Director Doctorate
2026-05-15
Requirements
  • 10+ years of experience developing and deploying AI/ML applications and delivering data-driven solutions at scale
  • Demonstrated experience leading and managing data science teams, including hiring, performance management, and talent development
  • Proven track record of building and scaling high-performing teams - including designing leveling frameworks, mentorship programs, and succession planning
  • Deep hands-on expertise in Generative AI, Large Language Models (LLMs), Agentic AI systems, and advanced NLP/Deep Learning techniques
  • Practical experience with LLM application design: prompt engineering, retrieval-augmented generation (RAG), model fine-tuning, tool use, and multi-agent orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen)
  • Graduate degree (Master's or PhD) in Computer Science, Engineering, Statistics, or a related quantitative discipline, or equivalent professional experience
  • Strong command of Python and core data science libraries (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow)
  • Deep understanding of CS fundamentals, computational complexity, and algorithm design
  • Experience architecting and delivering large-scale distributed systems in an agile environment, including rapid prototyping and iterative development
  • Excellent communication and stakeholder management skills - able to translate complex technical concepts for executive and non-technical audiences
Preferred
  • PhD in Computer Science with an AI/ML research focus and publications in top-tier venues
  • Experience in the healthcare or life sciences domain; familiarity with applying AI to pharmaceutical or market access data
  • Hands-on experience with AWS ML infrastructure: SageMaker, Lambda, S3, Snowflake, and related services
  • Experience with knowledge graphs, structured reasoning, and hybrid retrieval architectures
  • Prior experience operating at Director level or equivalent in a fast-paced, data-driven organization
Responsibilities
  • As Director of Data Science at Norstella, you will set the strategic vision for our data science capabilities and lead a high-performing team of data scientists and engineers. You will be a technical authority and a people-first leader - building talent, shaping culture, and delivering AI-powered solutions that have a direct impact on patient access to life-saving therapies.
  • Define and own the data science strategy, aligning closely with product, engineering, and executive leadership to drive roadmap prioritization
  • Lead, mentor, and grow a team of data scientists and ML engineers - fostering a culture of excellence, curiosity, and continuous learning
  • Build and develop talent: recruit top-tier data science professionals, design career development frameworks, and create pathways for growth at all levels
  • Champion the adoption of GenAI, Agentic AI, and LLM-powered architectures across the organization - defining reference frameworks for tool use, code interpretation, retrieval-augmented generation (RAG), and multi-agent workflows
  • Collaborate with product leadership to identify, elaborate, and prioritize high-impact projects
  • Oversee the delivery of AI-enabled microservices in collaboration with content and product engineering teams
  • Define and evolve engineering standards, best practices, and architectural patterns for scalable, production-grade AI systems
  • Stay at the cutting edge of AI/ML research; deliver regular presentations to internal stakeholders on emerging trends and their strategic implications
  • Partner cross-functionally to ensure data science solutions are operationalized effectively and drive measurable business value
  • All other duties, as assigned.
View full posting on CareerOneStop → ID: 53e9df0c11dc
Language Data Scientist, Alexa International
Amazon · Bellevue, WA
Mid-level Doctorate
2026-05-15
Requirements
  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • 1+ years of guiding and coaching a group of researchers experience
  • 1+ years of working with or evaluating AI systems experience
  • 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
  • Master's degree or above in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
  • Experience applying theoretical models in an applied environment
Preferred
  • Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in Python, Perl, or another scripting language
  • Experience in a ML or data scientist role with a large technology company
  • Experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience working on multi-team, cross-disciplinary projects
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication
Responsibilities
  • To be successful in this role, you must have a passion for data, efficiency, and accuracy. Specifically, you will:
  • Own data analyses for customer-facing features, including launch go/no-go metrics for new features and accuracy metrics for existing features
  • Handle unique data analysis requests from a range of stakeholders, including quantitative and qualitative analyses to elevate customer experience with speech interfaces
  • Lead and evaluate changing dialog evaluation conventions, test tooling developments, and pilot processes to support expansion to new data areas
  • Continuously evaluate workflow tools and processes and offer solutions to ensure they are efficient, high quality, and scalable
  • Provide expert support for a large and growing team of data analysts
  • Provide support for ongoing and new data collection efforts as a subject matter expert on conventions and use of the data
  • Conduct research studies to understand speech and customer-Alexa interactions
  • Collaborate with scientists and product managers, and other stakeholders in defining and validating customer experience metrics
View full posting on CareerOneStop → ID: eaa6ee5d0b4b
Senior Staff Research Data Scientist, Workspace GenAI
Google · Seattle, WA
Senior Doctorate
2026-05-15
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
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
Director, Data Science
Norstella · Olympia, WA
Director Doctorate
2026-05-15
Requirements
  • 10+ years of experience developing and deploying AI/ML applications and delivering data-driven solutions at scale
  • Demonstrated experience leading and managing data science teams, including hiring, performance management, and talent development
  • Proven track record of building and scaling high-performing teams - including designing leveling frameworks, mentorship programs, and succession planning
  • Deep hands-on expertise in Generative AI, Large Language Models (LLMs), Agentic AI systems, and advanced NLP/Deep Learning techniques
  • Practical experience with LLM application design: prompt engineering, retrieval-augmented generation (RAG), model fine-tuning, tool use, and multi-agent orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen)
  • Graduate degree (Master's or PhD) in Computer Science, Engineering, Statistics, or a related quantitative discipline, or equivalent professional experience
  • Strong command of Python and core data science libraries (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow)
  • Deep understanding of CS fundamentals, computational complexity, and algorithm design
  • Experience architecting and delivering large-scale distributed systems in an agile environment, including rapid prototyping and iterative development
  • Excellent communication and stakeholder management skills - able to translate complex technical concepts for executive and non-technical audiences
Preferred
  • PhD in Computer Science with an AI/ML research focus and publications in top-tier venues
  • Experience in the healthcare or life sciences domain; familiarity with applying AI to pharmaceutical or market access data
  • Hands-on experience with AWS ML infrastructure: SageMaker, Lambda, S3, Snowflake, and related services
  • Experience with knowledge graphs, structured reasoning, and hybrid retrieval architectures
  • Prior experience operating at Director level or equivalent in a fast-paced, data-driven organization
Responsibilities
  • As Director of Data Science at Norstella, you will set the strategic vision for our data science capabilities and lead a high-performing team of data scientists and engineers. You will be a technical authority and a people-first leader - building talent, shaping culture, and delivering AI-powered solutions that have a direct impact on patient access to life-saving therapies.
  • Define and own the data science strategy, aligning closely with product, engineering, and executive leadership to drive roadmap prioritization
  • Lead, mentor, and grow a team of data scientists and ML engineers - fostering a culture of excellence, curiosity, and continuous learning
  • Build and develop talent: recruit top-tier data science professionals, design career development frameworks, and create pathways for growth at all levels
  • Champion the adoption of GenAI, Agentic AI, and LLM-powered architectures across the organization - defining reference frameworks for tool use, code interpretation, retrieval-augmented generation (RAG), and multi-agent workflows
  • Collaborate with product leadership to identify, elaborate, and prioritize high-impact projects
  • Oversee the delivery of AI-enabled microservices in collaboration with content and product engineering teams
  • Define and evolve engineering standards, best practices, and architectural patterns for scalable, production-grade AI systems
  • Stay at the cutting edge of AI/ML research; deliver regular presentations to internal stakeholders on emerging trends and their strategic implications
  • Partner cross-functionally to ensure data science solutions are operationalized effectively and drive measurable business value
  • All other duties, as assigned.
View full posting on CareerOneStop → ID: 3149ede13fe7
Senior Data Scientist - GenAI/Python/AWS/SQL
Unum Group · Boise, ID
Senior Doctorate
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
Requirements
  • 6+ years of professional experience or equivalent relevant work.
  • Proven track record leading end-to-end data science projects with measurable business impact.
  • *Technical Expertise
  • *Core Data Science Capabilities (expert in at least two, strong in others):
  • Programming & Automation:
  • Python required; experience with automation, DevOps practices, APIs, file I/O, and database integrations.
  • Experience engineering solutions in cloud environments (AWS preferred; Azure/Google comparable).
  • Exposure to object-oriented development and scalable architecture.
  • Data Visualization:
  • Expertise across multiple visualization tools and techniques.
  • Ability to tailor visuals to business use cases and audiences.
  • Statistics & Machine Learning:
  • Deep knowledge of statistical inference, regression, feature selection, feature extraction, and ML algorithms.
  • Experience leading large-scale modeling projects end-to-end.
  • Familiarity with generative AI approaches is a plus.
  • Data Engineering / ETL:
  • Strong SQL skills; ability to design, debug, and optimize complex queries.
  • Ability to navigate and explore large databases independently.
  • Experience combining internal and external data sources.
  • *Soft Skills & Business Leadership
  • Strong communication skills, including the ability to influence senior leaders.
  • Project management expertise and strong business acumen (financial services experience a plus).
  • Ability to manage multiple concurrent initiatives in a fast-moving environment.
  • Comfortable leading engagements and representing analytics with executive leadership.
Education
  • Bachelor's degree in a quantitative field required.
  • Master's or PhD in a quantitative discipline preferred.
Responsibilities
  • *Analytical Solution Development
  • Design, develop, and execute analytical solutions using optimization, simulation, machine learning, generative AI, and statistical modeling.
  • Construct predictive models to explain events, forecast behaviors, identify risk, or perform segmentation and clustering.
  • Apply domain expertise to ensure models are practical, interpretable, and aligned with business needs.
  • Evaluate alternative approaches and select appropriate modeling techniques for each use case.
  • *Data Engineering & Preparation
  • Integrate and transform large volumes of data from diverse sources (e.g., DB2, SQL Server, Teradata, APIs) to support analytics and experimentation.
  • Build modeling-ready datasets using validation, reconciliation, feature engineering, and aggregation techniques.
  • Write complex SQL queries involving multi-table joins, data exploration, and troubleshooting with minimal guidance.
  • Develop logical data models combining internal and external datasets; lead conversations with external data providers when needed.
  • *Automation & Deployment
  • Build automated analytics pipelines leveraging scripting, APIs, DevOps practices, and cloud platforms.
  • Partner with engineering and IT teams to scale solutions, automate workflows, and integrate models into business processes.
  • Play a lead role in operationalizing AI/ML solutions within production environments.
  • *Visualization, Insights & Communication
  • Develop and deliver clear, compelling visualizations (static or dynamic) tailored to various audiences.
  • Interpret analytical results and communicate actionable insights that influence senior leaders and key business partners.
  • Translate complex technical work into business-friendly recommendations.
  • *Leadership, Mentorship & Collaboration
  • Coach, mentor, and develop junior data scientists; provide technical guidance and feedback.
  • Provide leadership on data science initiatives, ensuring outputs meet quality standards.
  • Work in a collaborative, innovation-focused environment with product owners, engineers, data architects, and business partners.
  • Manage multiple projects simultaneously, prioritizing independently and guiding less experienced team members.
  • *Innovation & Research
  • Stay current on emerging statistical methods, machine learning advancements, and generative AI tools.
  • Conduct independent R&D to prototype new approaches and explore innovative solutions for high-visibility business problems.
  • Demonstrate entrepreneurial, self-starter mindset with a strong curiosity and continuous-learning orientation.
  • Unum and Colonial Life are part of Unum Group, a Fortune 500 company and leading provider of employee benefits to companies worldwide. Headquartered in Chattanooga, TN, with international offices in Ireland, Poland and the UK, Unum also has significant operations in Portland, ME, and Baton Rouge, LA - plus over 35 US field offices. Colonial Life is headquartered in Columbia, SC, with over 40 field offices nationwide.
View full posting on CareerOneStop → ID: 161ff9376ec3
Data Scientist (Data Science)
The Boeing Company · Seattle, WA
Mid-level Doctorate
2026-05-14
Requirements
  • Familiarity with GPU compute infrastructure and distributed model training.
  • Familiarity with container technologies (e.g., Docker, Kubernetes).
  • Shape the direction of generative AI in a mission-critical organization.
  • Collaborate with a world-class team of engineers, scientists, and domain experts.
  • Access to cutting-edge infrastructure, models, and research partnerships.
  • Bachelor's degree in computer science, Machine Learning, Applied Mathematics, Computer Engineering, Software Engineering, Artificial Intelligence, Physics or a closely related field.
  • 3+ years of experience in data science or machine learning.
  • 3+ years of experience in programming in Python and familiarity with data engineering workflows (e.g., Spark, Airflow, SQL).
  • This position must meet U.S. export control compliance requirements. To meet U.S. export control compliance requirements, a "U.S. Person" as defined by 22 C.F.R. §120.62 is required.
  • "U.S. Person" includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asylee.
  • *Export Control Details:
  • US based job, US Person required
Preferred
  • Master's or PhD in Computer Science, Machine Learning, Applied Mathematics, Computer Engineering, Software Engineering, Artificial Intelligence, Physics or a closely related field
  • Experience fine-tuning open-source models and integrating APIs from commercial providers.
  • Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
  • Experience in AI ethics and governance in generative models.
  • Experience with data engineering tools (e.g., SQL, Spark
Education
  • Education/experience typically acquired through advanced technical education (e.g. Bachelor) and typically 5 or more years' related work experience or an equivalent combination of technical education and experience (e.g. PhD, Master+3 years' related work experience, 9 years' related work experience, etc.).
Responsibilities
  • At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.
  • *Boeing Defense, Space & Security (BDS) has an exciting opportunity for a Mid-Level Data Scientist - GenAI to join our team located in Seattle, WA or Arlington, VA.
  • *We are seeking a skilled and innovative Data Scientist to contribute to the development and optimization of advanced AI, Machine Learning (ML), and Generative AI (GenAI) models within BDS. This role offers the opportunity to learn and grow your skills in ML and large language models (LLMs). You will work closely with senior data scientists and cross-functional teams to contribute to AI-driven applications in our organization.
  • *Successful candidates will have:
  • Proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow).
  • Contribute to the development and deployment of models.
  • Design and implement pipelines for model fine-tuning and evaluation.
  • Develop prompt engineering strategies and embedding techniques to enhance model performance.
  • Prototype applications that address specific business needs.
  • Assist in model performance evaluation and bias/fairness assessments.
  • Collaborate with MLOps and engineering teams to support model scaling and monitoring.
  • Share knowledge of AI/ML/GenAI tools and trends with the team and contribute to best practices.
  • *This position is hybrid. The selected candidate will be required to perform some work onsite at one of the listed location options. This is at the hiring team's discretion and could potentially change in the future.
  • *This position is for 1st shift.
  • *This position must meet export control compliance requirements. To meet export control compliance requirements, a "U.S. Person" as defined by 22 C.F.R. §120.15 is required. "U.S. Person" includes U.S. Citizen, lawful permanent resident, refugee, or asylee.
View full posting on CareerOneStop → ID: 7d65307bce22
Machine Learning - Compiler Engineer II, Annapurna Labs
Amazon · Seattle, WA
Mid-level Doctorate
2026-05-14
Requirements
  • 3+ years of non-internship professional software development experience
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience programming with at least one software programming language
  • 3+ years of non-internship professional software development, or 3+ years of software development experience
  • 2+ years of experience architecting and optimizing compilers
  • Proficiency with 1 or more of the following programming languages: C++ (preferred), C, Python
Preferred
  • 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent
  • PhD in computer science, computer engineering, or related field, or MS degree
  • Experience with multiple toolchains and Instruction Set Architectures
  • Proficiency with resource management, scheduling, code generation, and compute graph optimization
  • Experience optimizing Tensorflow, PyTorch or MxNET deep learning models
View full posting on CareerOneStop → ID: a724fa94a580
Senior Machine Learning Engineer - Earner Incentive
Uber · Seattle, WA
Senior Doctorate
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
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
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
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
Machine Learning Engineer II, Pricing
Uber · Seattle, WA
Mid-level Doctorate
2026-05-13
Requirements
  • Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
  • 2+ years of experience in developing and deploying machine learning models and optimization algorithms in large-scale production environments
  • Proficiency in programming languages such as Python, Scala, Java, or Go
  • Experience with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
  • Experience in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
  • Familiarity with modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. LP, convex optimization), combined with proven ability and ambition to continuously deepen expertise in these areas
Preferred
  • Experience in translating ambiguous business problems into technical solutions in a structured and principled way
  • Strong communication skills, including through documentation and design discussions
  • Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavio
  • Experience in reinforcement learning and causal machine learning
  • For New York, NY-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.
Responsibilities
  • Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders.
  • We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.
  • *What You Will Do
  • Design, develop, and productionize end-to-end ML solutions for large-scale distributed systems serving billions of trips
  • Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
  • Partner with senior engineers to plan the scope and execution of projects and mentor junior team members on design and implementation
  • Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems
View full posting on CareerOneStop → ID: c8b958526340
Senior Machine Learning Manager, Search & Knowledge Platform
Apple · Seattle, WA
Manager Doctorate
2026-05-13
Requirements
  • 8+ years of experience in leading engineering/applied research/ML experiences in natural language processing, SOTA generative AI models
  • Proven record of consistent delivery of technology/products across the full Machine Learning life cycle
  • MS or Ph.D. in Computer Science, Machine Learning, information retrieval, data mining, or a related field
Preferred
  • Strong background and experience in Machine Learning, NLP, and RAG.
  • Strong engineering and R&D experience in LLM post-training, advanced RL-based methods to improve LLM models' safety and quality using RLHF/RLAIF, reward model, advanced RL policy optimization algorithms, cutting-edge hallucination reduction methods, and their engineering implementation, hands-on experience to develop and ship RL based models with high availability, low latency, robustness, and stability.
  • Exceptional verbal and written communication skills to lead
  • Excellent product vision and sound business acumen. Ability to manage long-term strategy and short-term deliverables.
  • Strong engineering leadership and fundamentals.
Responsibilities
  • Apple is where individual imaginations gather together, contributing to the values that lead to great work. Every The AI, Search & Knowledge Platforms team builds amazing products and services for Apple's customers while serving as a foundational partner to teams across Apple. The team delivers world-class AI, search, and knowledge systems powering Siri, Apple Intelligence, Safari, and iMessage, and operates the foundational platforms and infrastructure that keep these intelligent experiences running at hyperscale.
  • You will lead the strong team of MLE, SWE, and data engineers responsible for delivering efficient and effective Generative AI models to build and improve the summarization capabilities across different data types.
  • In this role, you'll drive E2E R&D and engineering to generate high-quality summaries and experiences for Apple users. This includes on-device LLM models for personal content summarization across 1P and 3P apps, and powerful summarization models on Apple's Private Cloud Compute servers. In addition, improve the summarization models' quality for world knowledge-seeking questions and Safari pages to provide accurate answers and highlight web page gists in real-time. Lead the team to develop SOTA LLM-based generative models, groundedness models, and safety models for accurate, grounded, concise, and safe summaries. Develop sophisticated on-device and on-server software frameworks for context integration fast and cost-efficient LLM-based model inference. Integrate the Apple ecosystem with Apple's LLM infrastructure and generative models to deliver delightful user experiences. Devise the product vision and strategy and execute the plan to deliver the highest quality end-user experience. Collaborate with various organizational partners to profoundly impact billions of Apple users worldwide.
View full posting on CareerOneStop → ID: 01ef76150873
Sr Machine Learning Engineer, Pricing
Uber · Seattle, WA
Senior Doctorate
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
Requirements
  • Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
  • 6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters
  • Proficiency in programming languages such as Python, Scala, Java, or Go
  • Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
  • Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
  • Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavio
  • Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization)
Preferred
  • Experience developing multi-year technical strategies and cross-team platform architecture, and proficiency owning technical roadmap and leading complex technical projects while substantially influencing the scope and output of others
  • Track record of translating complex business problems into technical solutions and driving multi-functional projects across multiple teams
  • Excellent communication skills to lead initiatives across multiple product areas and collaborate effectively with cross-functional teams
  • Proficiency in reinforcement learning and causal machine learning
  • For New York, NY-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.
Responsibilities
  • Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders.
  • We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.
  • *What You Will Do
  • Drive technical strategy and roadmap ownership over a 1+ year horizon and own the implementation, including platform-level architecture decisions, executive communication and alignment, technical mentorship, and cross-team technical influence
  • Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips
  • Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
  • Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems
View full posting on CareerOneStop → ID: 012994d721c5
Director, Data Science - AI for Work (AI4W) Ecosystem
Meta · Olympia, WA
Director Doctorate
2026-05-13
Requirements
  • Director, Data Science - AI for Work (AI4W) Ecosystem Responsibilities:
  • Collaborate with Engineering, Product, and cross-functional teams to inform, influence, support, and execute strategy and investment decisions for Meta.
  • Contribute to the long-term technical vision and strategy for analytics methods and metrics to enhance the quality and efficiency of our platforms at scale.
  • Work with engineering and other data scientists to build and improve AI development, automation, experimentation, and measurement methods and metrics, ensuring high-quality throughput and impact.
  • Develop an understanding of complex, large-scale AI development, experimentation, and measurement systems, as well as broader industry challenges, to identify current and future risks and opportunities.
  • Inspire, and lead a team of data scientists and managers across multiple teams in close collaboration with other Data Science Directors and Managers.
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 10+ years of work experience leading analytics work in IC capacity, working collaboratively with Engineering and cross-functional partners, and guiding data-influenced product planning, prioritization and strategy development
  • Experience working effectively with multiple stakeholders and cross-functional teams, including Engineering, PM/TPM, Analytics and Finance
  • Experience framing and communication skills
Preferred
  • Masters or Ph.D. Degree in a quantitative field
  • Experience with predictive modeling, machine learning, and experimentation/causal inference methods
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Responsibilities
  • AI for Work (AI4W) is Meta's company-wide effort to integrate AI into every tool, team, and process at Meta. This role will be the founding senior IC on a new "AI4W Ecosystem" analytics team.We are seeking a Data Science Director (IC) who is passionate about developing, measuring, and strategizing investments of Meta's products. As a Data Scientist, you will collaborate with cross-functional partners to identify and solve complex problems using data and analysis. Your role will involve shaping product development, quantifying new opportunities, and ensuring products bring value to users and the company. You will guide teams using data-driven insights, develop hypotheses, and employ rigorous analytical approaches to test them. You will tell data-driven stories, present clear insights, and build credibility with stakeholders. By joining our team, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.
View full posting on CareerOneStop → ID: 78590a86e3e2
Director, Data Science - AI for Work (AI4W) Ecosystem
Meta · Olympia, WA
Director Doctorate
2026-05-13
Requirements
  • Director, Data Science - AI for Work (AI4W) Ecosystem Responsibilities:
  • Collaborate with Engineering, Product, and cross-functional teams to inform, influence, support, and execute strategy and investment decisions for Meta.
  • Contribute to the long-term technical vision and strategy for analytics methods and metrics to enhance the quality and efficiency of our platforms at scale.
  • Work with engineering and other data scientists to build and improve AI development, automation, experimentation, and measurement methods and metrics, ensuring high-quality throughput and impact.
  • Develop an understanding of complex, large-scale AI development, experimentation, and measurement systems, as well as broader industry challenges, to identify current and future risks and opportunities.
  • Inspire, and lead a team of data scientists and managers across multiple teams in close collaboration with other Data Science Directors and Managers.
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 10+ years of work experience leading analytics work in IC capacity, working collaboratively with Engineering and cross-functional partners, and guiding data-influenced product planning, prioritization and strategy development
  • Experience working effectively with multiple stakeholders and cross-functional teams, including Engineering, PM/TPM, Analytics and Finance
  • Experience framing and communication skills
Preferred
  • Masters or Ph.D. Degree in a quantitative field
  • Experience with predictive modeling, machine learning, and experimentation/causal inference methods
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Responsibilities
  • AI for Work (AI4W) is Meta's company-wide effort to integrate AI into every tool, team, and process at Meta. This role will be the founding senior IC on a new "AI4W Ecosystem" analytics team.We are seeking a Data Science Director (IC) who is passionate about developing, measuring, and strategizing investments of Meta's products. As a Data Scientist, you will collaborate with cross-functional partners to identify and solve complex problems using data and analysis. Your role will involve shaping product development, quantifying new opportunities, and ensuring products bring value to users and the company. You will guide teams using data-driven insights, develop hypotheses, and employ rigorous analytical approaches to test them. You will tell data-driven stories, present clear insights, and build credibility with stakeholders. By joining our team, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.
View full posting on CareerOneStop → ID: 5466a2cf6504
Senior Data Scientist, Special Projects
Amazon · Seattle, WA
Senior Doctorate
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
Requirements
  • 2+ years of experience in data analysis.
  • 1+ years of programming experience.
  • Significant experience working with large, complex data sets and common data science tools.
  • Experience working with database Python.
  • Experience designing, building, deploying, and validating machine-learning predictive models, ideally within a business framework.
  • Experience training multi model design to structure and train for unstructured data matching.
  • Experience training LLM models for specialized use cases
  • *COMPETENCIES - SKILLS/KNOWLEDGE/ABILITIES:
  • Highly inquisitive and self-motivated.
  • Ability to map out solutions with a starting point and end goal, but with few steps identified in-between.
  • Exceptional ability to analyze and synthesize data.
  • Advanced proficiency in SQL and Python.
  • Competency navigating and working within the AWS cloud suite.
  • Competency designing self-learning models that result in logarithm trends to identify trends in data to predict potential outcomes or missing data fields.
  • Core understanding of statistical concepts and methods.
  • Competency in the MS Office Suite.
  • Highly accountable and inquisitive, able to manage multiple tasks in a fast-paced, dynamic environment.
  • Self-motivated.
  • Excellent communication skills (written, verbal, and interpersonal) to coordinate across teams and deliver polished presentations.
  • Experience with training NumPy and Pandas models.
Education
  • PHD degree required in a Quantitative (heavy in mathematics, statistics or analysis, such as Applied Mathematics, Optimization, Psychology, or Economics) or Programming discipline.
Responsibilities
  • Conduct advanced analyses and statistical deep dives, with a focus on producing actionable recommendations and strategic guidance for decision makers.
  • Develop and deploy custom models and algorithms using data and machine learning libraries to solve complex business problems.
  • Mine, clean, process, transform and join data from a variety of sources including SQL servers, AWS environments, Azure, SnowFlake, SalesForce, internal systems, and flat files.
  • Identify, wrangle, scrape, and assemble new data sources from the web, data aggregators, and public sources.
  • Build rich, interactive dashboards and visualizations from the ground up using PowerBI.
  • Compile and present key findings and reports to all levels of the organization, including senior leadership.
  • Continuously seek out opportunities to add value through process automation and programmatic solutions to manual tasks and monitor and improve Data Science model performance.
  • Act as a subject matter expert within the data science field. Continuously learn, grow, and explore new emerging technologies. (Stay up to date with industry trends and best practices.
  • Problem-solve, generate new ideas, and provide creative solutions.
  • Mentor, model, act as a resource, and provide guidance for more junior analysts and team members.
  • Lead development, testing and implementation of machine-learning models and algorithms using data and machine learning to solve complex business problems.
View full posting on CareerOneStop → ID: 148da44b0a7b
Data Scientist/Statistician
Intel · Hillsboro, OR
Mid-level Doctorate
2026-05-12
Requirements
  • You must possess the minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
  • Master's or PhD degree in Statistics, Data Science or Industrial Engineering.
  • 4+ years working in statistics or data science
  • 2+ years working on quality systems such as process control systems and change control systems
  • 1+ year working on PowerBI or similar dashboards
  • 1+ years in data analytics and machine learning (Python, R, JMP, etc.) and relational databases (SQL).
Preferred
  • 1+ years working on fault detection systems
  • 2+ years in a Technical leadership role.
  • 3+ months working knowledge with any of following technologies: JSL, Python, Spark, NiFi, Hadoop, HBase, S3 object storage, Kubernetes, REST APIs and services.
  • 3+ months working knowledge with CI/CD (Continuous Integration/Continuous Deployment) and proficiency with GitHub and GitHub Actions.
  • Prior interaction with factory automation systems
  • Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.
Responsibilities
  • Intel Foundry Statistics and Data Science team's mission is to drive statistically sound methodologies into business practices and systems to help organization manage change control decisions, monitor capability of the process, ensure matching across tools and fabs, and drive best in class process control systems. Our team reports into the foundry quality and reliability team and is essential for driving transformation of Intel to be focused on not just process development, but a great partner for our foundry customers to help turn data into information. Our team is looking for an engineer with background in statistics and data science with strong technical skills in applied statistics, good communication skills, ability to also help support and develop modern AI/ML solutions.
  • As a Statistician and Data Scientist in the TD AI office, you will partner with Intel's factory automation organization and Foundry TD's functional areas to support semiconductor process development and transfer of these systems to worldwide virtual factory network.
  • The primary responsibilities for this role will include, but are not limited to:
  • Ensuring organization leverages appropriate data and analyses to make change control decisions
  • Drives organization to use process control systems to improve capability, matching, and stability of semiconductor process technologies
  • Use predictive modeling, statistics, Machine Learning, Data Mining, and other data analysis techniques to collect, explore, and extract insights from the structure and unstructured data.
  • Develop software, algorithms and applications to apply mathematics to data, perform large scale experimentation and build data driven apps to translate data into intelligence, solve a variety of business problems and enable business strategy.
  • Assist the business with casual inferences; observations with finding patterns and relationships in data.
  • Interfacing with process and integration functional area analytics teams to help solve problems
  • A successful candidate will have proven experience demonstrating the following skills and behavioral traits:
  • Experience in using AI/ML/Analytics algorithms and methodologies
  • Developing statistical methodologies
  • Ability to code statistical analysis, data cleaning, and data manipulation via common languages such as JSL, Python, and SQL
  • Understanding of data structures
  • Strong written and oral communication skills.
  • Ability to train others
  • Analytical problem solving and troubleshooting skills.
  • Teamwork skills and partnership skills.
  • High tolerance of ambiguity.
  • High level of self-motivation
View full posting on CareerOneStop → ID: 8ef4c4eed089
Data Scientist II, Amazon Stores Security
Amazon · Seattle, WA
Mid-level Doctorate
2026-05-10
Requirements
  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Preferred
  • Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
  • Experience in Python, Perl, or another scripting language
  • Experience effectively communicating complex concepts through written and verbal communication
Responsibilities
  • Demonstrate thorough technical knowledge on feature engineering of massive datasets, effective exploratory data analysis, and model building using industry standard AI/ML models and working with Large Language Models
  • With your broad expertise in a variety of data science disciplines, recommend the right data science strategy and drive solution to complex or ambiguous problems
  • Work closely with internal stakeholders like the business teams, engineering teams and partner teams, influence their strategies to align with your focus area
  • Innovate by adapting new modeling techniques and procedures
  • Passionate about working with huge data sets ( training/fine tuning) and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets
  • Exposure at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive.
  • Show good judgment when making trade-offs between short-term customer, market, or research needs and long-term operations or technology needs.
View full posting on CareerOneStop → ID: 6ae2fbb77b15
Data Scientist II, Long Term Planning and Forecasting
Amazon · Bellevue, WA
Mid-level Doctorate
2026-05-10
Requirements
  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • 1+ years of guiding and coaching a group of researchers experience
  • 1+ years of working with or evaluating AI systems experience
  • 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
  • Experience applying theoretical models in an applied environment
Preferred
  • Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in Python, Perl, or another scripting language
  • Experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience effectively communicating complex concepts through written and verbal communication
  • Experience in forecasting analyses
Responsibilities
  • As a Data Scientist in LTPF (Long-Term Planning & Forecasting):
  • You will develop causal inference models, automated explainability frameworks, and variance bridging methodologies that translate LTPF's forecasts and plans into actionable business intelligence.
  • Your work will enable leadership to understand why forecasts and actuals diverge, what is driving demand shifts, and how strategic decisions propagate through the planning ecosystem.
  • You will build automated Plan-vs-Actual and Actual-vs-Actual variance decomposition models that quantify the contribution of individual demand drivers to observed gaps across revenue, price, units, inventory, and capacity metrics at multiple granularities to serve audiences from working-level analysts to VP-level planning reviews cycles.
  • You will build and maintain a causal model library with standardized hypothesis generation and validation pipelines, applying techniques from causal inference, time-series econometrics, and Bayesian methods. Each model will include calibrated confidence scoring and reusable components that scale across worldwide marketplaces.
  • You will develop GenAI-powered narrative generation capabilities that synthesize quantitative variance outputs into human-readable performance summaries and design automated hypothesis ranking to determine which demand drivers are most responsible for observed forecast error.
  • Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
  • The benefits that generally apply to regular, full-time employees include:
  • Medical, Dental, and Vision Coverage
  • Maternity and Parental Leave Options
  • Paid Time Off (PTO)
  • If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
  • At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!
View full posting on CareerOneStop → ID: 39530c4e672c
Data Scientist II, Long Term Planning and Forecasting
Amazon · Bellevue, WA
Mid-level Doctorate
2026-05-10
Requirements
  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • 1+ years of guiding and coaching a group of researchers experience
  • 1+ years of working with or evaluating AI systems experience
  • 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
  • Experience applying theoretical models in an applied environment
Preferred
  • Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in Python, Perl, or another scripting language
  • Experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience effectively communicating complex concepts through written and verbal communication
Responsibilities
  • As a Data Scientist in LTPF (Long-Term Planning & Forecasting):
  • You will develop causal inference models, automated explainability frameworks, and variance bridging methodologies that translate LTPF's forecasts and plans into actionable business intelligence.
  • Your work will enable leadership to understand why forecasts and actuals diverge, what is driving demand shifts, and how strategic decisions propagate through the planning ecosystem.
  • You will build automated Plan-vs-Actual and Actual-vs-Actual variance decomposition models that quantify the contribution of individual demand drivers to observed gaps across revenue, price, units, inventory, and capacity metrics at multiple granularities to serve audiences from working-level analysts to VP-level planning reviews cycles.
  • You will build and maintain a causal model library with standardized hypothesis generation and validation pipelines, applying techniques from causal inference, time-series econometrics, and Bayesian methods. Each model will include calibrated confidence scoring and reusable components that scale across worldwide marketplaces.
  • You will develop GenAI-powered narrative generation capabilities that synthesize quantitative variance outputs into human-readable performance summaries and design automated hypothesis ranking to determine which demand drivers are most responsible for observed forecast error.
  • Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
  • The benefits that generally apply to regular, full-time employees include:
  • Medical, Dental, and Vision Coverage
  • Maternity and Parental Leave Options
  • Paid Time Off (PTO)
  • If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
  • At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!
View full posting on CareerOneStop → ID: 5953602d6eef
Principal Data Scientist & Analytics
Microsoft Corporation · Redmond, WA
Senior Doctorate
2026-05-10
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
Machine Learning Engineer, Offline Infrastructure (Entry-Level / New Grad PhD)
Unity Technologies · Bellevue, WA
Entry-level Doctorate
2026-05-09
Requirements
  • PhD in Computer Science, Machine Learning, Systems, or a related field
  • Strong foundation in machine learning systems, distributed systems, or large-scale data processing (through research or projects)
  • Experience with Python and working with data-intensive workloads
  • Familiarity with ML frameworks (e.g., PyTorch, TensorFlow) and/or distributed systems (e.g., Ray, Spark)
  • Experience (academic or applied) with data pipelines, model training workflows, or large datasets
  • Strong problem-solving skills and ability to translate research ideas into practical systems
  • Interest in building scalable, reliable infrastructure for machine learning
  • Experience with workflow orchestration systems (Airflow, Flyte, etc.)
  • Exposure to large-scale data platforms (data lakes, warehouses, streaming systems)
  • Publications or research in ML systems, distributed systems, or related areas
  • *Additional information
  • Relocation support is not available for this position
  • Work visa/immigration sponsorship is not available for this position
Responsibilities
  • *The opportunity
  • Unity Vector builds an offline ML platform that powers insight, experimentation, attribution, and AI-driven decision-making across the company.
  • Our systems operate at scale across batch and streaming data, supporting analytics, product intelligence, machine learning pipelines, and business operations. As data volume and complexity grow, our platform enables large-scale model training, feature generation, and experimentation workflows that power production ML systems.
  • We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent PhD graduate who is excited to work on large-scale systems and apply research-driven thinking to real-world machine learning problems.
  • You'll help build and evolve the infrastructure that powers training data generation, ML workflows, and distributed model training. Working closely with experienced engineers and researchers, you'll contribute to systems that ensure our ML pipelines are reliable, scalable, and efficient.
  • This role offers the opportunity to bridge research and production-translating advanced ideas into systems that operate at scale.
  • Build and maintain data pipelines that generate training datasets for machine learning models and experimentation
  • Contribute to infrastructure that supports distributed training workflows (e.g., PyTorch, Ray)
  • Work with workflow orchestration tools (e.g., Airflow, Flyte, or similar) to support multi-stage ML pipelines
  • Improve reproducibility and reliability through dataset validation, monitoring, and testing
  • Partner with ML engineers to support experimentation and model iteration
  • Help optimize performance and efficiency across data processing and training systems
  • Contribute to the evolution of our offline ML platform architecture as it scales
View full posting on CareerOneStop → ID: 84abcebe5f20
Manager, Machine Learning Infrastructure - SIML
Apple · Seattle, WA
Manager Doctorate
2026-05-09
Requirements
  • Bachelor's, Master's, or Ph.D. in Computer Science, Computer Engineering, or a related field (or equivalent experience)
  • 7+ years of software engineering experience, with 2+ years in a technical leadership or management role
  • Strong programming skills in one or more of: Python, Java, Go, C/C++ Solid understanding of machine learning fundamentals and ML system workflows
  • Proven experience in building and scaling distributed systems and backend infrastructure
  • Strong system design skills with expertise in at least one systems domain (e.g., data infrastructure, distributed systems, ML platforms)
Preferred
  • Experience building infrastructure for ML workflows (data pipelines, training systems, evaluation frameworks, or deployment systems)
  • Domain experience in areas such as AI/ML, computer vision, NLP, or related fields
  • Experience working with large-scale datasets and compute-intensive systems
  • Experience improving developer productivity through tooling and platform abstractions
  • Ability to operate effectively in cross-functional, fast-paced environments with evolving requirements
Responsibilities
  • Do you think Computer Vision and Machine Learning can change the world? Do you think it can transform the way millions of people collect, discover and share the most special moments of their lives? We truly believe it can. And we are looking for hardworking engineers who can contribute to building the ecosystem of tooling necessary to create these exciting technologies.
  • We are the System Intelligent and Machine Learning (SIML) group that provides foundational computer vision and machine learning technologies to Apple's ecosystem. Our work is behind essential features such as Camera, Text & Handwriting recognition, and Apple Intelligence experiences (Image Playground, Writing Tools, Smart Script, Math Notes..). We are seeking an Engineering Manager to lead the development of scalable, high-performance infrastructure that powers product-focused machine learning initiatives.
  • In this role you will lead a team responsible for building and operating infrastructure that enables large-scale data processing (terabytes and beyond) across domains such as image generation, large language models (LLMs), computer vision, natural language processing, human-computer interaction, and text recognition. This includes designing systems for dataset creation and management, ingesting annotated and inferred data, and delivering seamless access to high-quality data for ML researchers and engineers.
  • A key part of this role is driving systems that enable deeper understanding of model behavior-such as failure mode analysis, evaluation pipelines, and benchmarking frameworks-to accelerate iteration velocity and improve model quality. You will work across the stack, tackling challenges ranging from low-level distributed systems and compute efficiency to building stable, intuitive interfaces for internal users.
  • As a leader, you will partner closely with cross-functional teams including ML researchers, product teams, and platform engineering to define roadmaps, align priorities, and deliver impactful solutions. You will play a critical role in shaping how ML systems are developed, evaluated, and scaled from early experimentation to production.
View full posting on CareerOneStop → ID: d0fb3fc55c81
Data Scientist, WW Ops FP&A
Amazon · Bellevue, WA
Mid-level Doctorate
2026-05-08
Requirements
  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • 1+ years of guiding and coaching a group of researchers experience
  • 1+ years of working with or evaluating AI systems experience
  • 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
  • Experience applying theoretical models in an applied environment
Preferred
  • Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in Python, Perl, or another scripting language
  • Experience in a ML or data scientist role with a large technology company
  • Experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience working on multi-team, cross-disciplinary projects
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication
Responsibilities
  • Own and solve difficult business problems where the solution approach is unclear, delivering high-quality artifacts that directly influence financial decisions for senior leadership
  • Apply a range of data science methodologies (statistical modeling, machine learning, time series analysis, econometrics) to solve complex forecasting challenges
  • Design and implement scalable, reliable approaches to extract insights from large, complex datasets across multiple domains
  • Develop metrics to quantify the benefits of solutions and measure project progress and success
  • Design and implement Retrieval-Augmented Generation (RAG) systems and LLM-based solutions to enhance financial knowledge retrieval and decision support
  • Proactively identify and solve challenges related to GenAI solutions including accuracy, latency, and context management
  • Partner with finance stakeholders, engineers, and other scientists to identify data requirements and deliver solutions that meet customer needs
  • Write clear, factually correct documents with substantial analytical components; explain technical concepts to non-technical audiences
  • Provide peer feedback on solutions and results; mentor and teach less experienced data scientists
View full posting on CareerOneStop → ID: 3ec0f3cbe7a2
Machine Learning Engineer, Search & Knowledge Quality
Apple · Seattle, WA
Mid-level Doctorate
2026-05-08
Requirements
  • BSc or Masters degree in Machine Learning, Data Science, Computer Science, Information Security, Mathematics, Statistics, or related field.
  • 3+ years of industry related experience, working in collaborate environments
  • Experience with programming skills in Python,C/C++, GoLand
  • Experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, AXLearn and Scikit-learn.
  • Familiarity with integrating ML solutions into production systems and existing workflows at scale; experience with CI/CD workflows and ML pipelines .
  • Excellent written and verbal communication skills, with the ability to present technical concepts clearly to varied audiences.
  • Strong problem-solving skills and ability to work independently as well as in a team environment.
Preferred
  • Ph.D. in a related field.
  • Experience with state-of-the-art ML methodologies, including LLM fine-tuning, neural network optimization , RL
  • Strong communication and accountability skills; a hard-working, strong work ethic, and collaboration abilities.
  • Experimental rigor when training/evaluating LLMs for the purpose of benchmarking LLM optimization algorithms.
Responsibilities
  • The Search and Knowledge Quality team is redefining how hundreds of millions of users interact with their devices to access information. We are an Applied Machine Learning team pushing the boundaries of artificial intelligence-from query understanding and information retrieval to response ranking and contextual answer generation.
  • Our team drives innovation by conducting research, building end-to-end solutions, and deploying them at scale to deliver meaningful customer impact across Apple products.
  • In this role, you will leverage and advance state-of-the-art LLM and ML techniques to better understand user queries and intent, improve document ranking, and generate high-quality answers. You will have end-to-end ownership of features within the Siri Search system, from ideation through production deployment. You will collaborate with industry-leading experts and cross-functional teams across multiple geographies, tackling complex challenges at scale.
View full posting on CareerOneStop → ID: 182f9a6dd20c
Principal Data Scientist
Microsoft Corporation · Redmond, WA
Senior Doctorate
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
Data Scientist, AWS Quick Data
Amazon · Seattle, WA
Mid-level Doctorate
2026-05-07
Requirements
  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • 1+ years of working with or evaluating AI systems experience
  • 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
  • Experience applying theoretical models in an applied environment
Preferred
  • Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in a ML or data scientist role with a large technology company
  • Experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience working on multi-team, cross-disciplinary projects
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication
Responsibilities
  • In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions.
  • Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features
  • Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings
  • Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases
  • Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance
  • Develop and refine annotation guidelines and quality frameworks for evaluation tasks
  • Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies
  • Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements
  • Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts
  • Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets
View full posting on CareerOneStop → ID: 451bab6bcd6d
Research Data Scientist, Chrome
Google · Seattle, WA
Mid-level Doctorate
2026-05-07
Requirements
  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  • 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
Preferred
  • 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
Responsibilities
  • Chrome's mission is to make the web work better for you. We do this by evolving Chrome, which serves the world and Google as both a product (4 billion plus clients) and a platform (that is: Chromium and related components that advance the open web and open media technologies).
  • As a platform, Chrome envisions a fast, safe, capable platform and thriving web for generations of users and developers. As a product, Chrome imagines a more helpful, adaptive agent that helps people with their multifaceted needs. Chrome's goal is to redefine browsing by delivering unparalleled safety, speed, efficiency, and ease of use, and integrating with Generative Artificial Intelligence (GenAI) and Google's web products, to understand user needs and provide personalized experiences.
  • In this role, your work will have tremendous impact throughout Chrome, as you will have an opportunity to work with the many teams that use our systems to gate features and understand users.You will blend research and product expertise to manage issues.
  • You will leverage a mix of theoretical and practical knowledge in advanced statistical and machine learning (ML) techniques, predictive modeling, human evaluation, experimentation, forecasting, exploratory analysis, and more to drive data-informed innovation, unlock opportunities, and enhance user experiences within Chrome.The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
  • Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .
  • Leverage advanced statistical methods on massive, datasets to extract insights from billions of events and thousands of features across organizational sources.
  • Analyze intricate product and platform usage patterns, translating data-driven insights into actionable product strategy and engineering decisions.
  • Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
  • Navigate technical or methodological conversations and narrative-telling presentations. Make clear, concise product and engineering recommendations to drive major impact. Use coding and methodology.
  • Demonstrate an interest and aptitude in data, metrics, analysis, and trends, and applied knowledge of measurement, statistics, and program evaluation.
  • Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
View full posting on CareerOneStop → ID: 45c9a2be5971
Senior Data Scientist - AI & ML | MLOps Enablement (Hybrid - Seattle, WA)
Nordstrom · Seattle, WA
Senior Doctorate
2026-05-07
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
Data Scientist
Actalent · Bothell, WA
Mid-level Doctorate
2026-05-06
Requirements
  • PMS or equivalent in computational biology, bioinformatics, biostatistics, computer science, genomics or a related field with postdoctoral research experience in Cancer Biology; or MS in cancer biology or related field with established advanced capability and track record in developing and applying computational and bioinformatics methods.
  • Five years or more of post-PhD academic and/or industry experience working with large, multidimensional, genomics datasets (e.g. NGS, RNA-Seq, transcriptomics, proteomics, flow cytometry, etc.)
  • Strong foundation in molecular biology and next-generation sequencing technologies (DNA-seq, RNA-seq, targeted panels, WES/WGS)
  • NGS Data Analysis
  • Hands-on experience analyzing NGS data end-to-end, including:
  • o Raw data processing and quality control (FASTQ, BAM/CRAM)
  • o Alignment, variant calling, and/or expression quantification
  • o Annotation and interpretation of variants or molecular signatures
  • Familiarity with common NGS tools and frameworks (e.g., BWA, Bowtie2, GATK, SAMtools, Picard, STAR, Salmon, Kallisto)
  • Pipeline Development & Automation
  • Proven experience developing, optimizing, and maintaining reproducible bioinformatics pipelines
  • Familiarity with workflow management systems (e.g., Nextflow, Snakemake, WDL/Cromwell)
  • Strong scripting and automation skills in Bash, Python, and R.
  • Software & Data Engineering
  • Experience writing code versioned with Git/GitHub
  • Ability to design modular, scalable, and maintainable analytical workflows
  • Familiarity with containerization technologies (Docker, Singularity/Apptainer)
  • Statistical & Computational Skills
  • Solid understanding of statistics and applied methods relevant to genomics (e.g., differential expression, QC metrics, batch effects)
  • Experience with data visualization and reporting for scientific and non-scientific audiences
  • Ability to assess analytical performance, accuracy, and robustness
  • Computing Environments
  • Experience working in Linux/Unix environments
  • Familiarity with high performance computing (HPC) clusters and/or cloud platforms (AWS, GCP, Azure)
  • Understanding of data storage, data transfer, and compute optimization in large-scale datasets
  • Experience supporting product development, diagnostics, or translational research in an industry setting
  • Familiarity with assay validation concepts, analytical performance metrics, and documentation requirements
  • Exposure to regulated or quality-driven environments (e.g., CLIA, CAP) is a strong plus
  • Collaboration & Communication
  • Ability to clearly communicate technical results, assumptions, and limitations to cross functional teams
  • Experience collaborating with wet lab scientists, software engineers, and program partners
  • Strong documentation skills for pipelines, analyses, and standard operating procedures
Responsibilities
  • The Bioinformatics Scientist Contractor will support the Translational Pathology Biomarker Testing Laboratory (TPBTL) within the Translational Medicine department.
  • The Bioinformatics Scientist applies advanced computational and statistical methods to analyze next generation sequencing (NGS) data to support research, clinical, or translational objectives. This role is responsible for developing, validating, and maintaining scalable, production-ready bioinformatics pipelines
  • for genomic, transcriptomic, and other high-throughput sequencing applications. Working in a highly collaborative environment, the Bioinformatics Scientist partners closely with wet-lab scientists, pathologists, and bioinformatics team to support data-driven decision-making in both research and CLIA regulated environments.
View full posting on CareerOneStop → ID: 73f2a8b90959
Machine Learning Engineer III
Indeed · Seattle, WA
Mid-level Doctorate
2026-05-06
Responsibilities
  • As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the team, and guide other members of the team to achieve product/technical goals. On a daily basis, you will explore data and formulate problem statements, develop and deploy predictive models while monitoring them in production, and guide the team on the same. Additionally, you will partner with cross-functional teams, evangelize your team's work, and stay updated with the latest advancements in the field.
  • Partner with cross-functional teams to enhance and optimize search algorithms for improved accuracy, relevance, and overall user experience.
  • Experiment with Proof of Concept Machine Learning model improvements, scale them to production, and run iterative A/B experiments to improve our matching technology while partnering with other teams
  • Define and clarify project priorities, deliverables, and success criteria in partnership with cross-functional teams.
  • Act as a bridge between technical and non-technical collaborators, facilitating effective communication and comprehension of project goals and outcomes.
  • Mentor and grow other software engineers and Machine Learning Engineers across teams
  • Break down larger Machine Learning initiatives into pieces that deliver incremental business value and guide the team through implementing them
  • Represent Indeed at major Machine Learning conferences, such as Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the International Conference on Learning Representations (ICLR).
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
  • Prior success in deploying impactful Machine Learning solutions to large-scale production systems, while partnering across teams
  • Solid knowledge of data structures and algorithms
  • Sense of ownership and accountability as a key contributor in the technical and product domains
  • Knowledge and practical experience working on Deep Learning Libraries (like Torch, Tensorflow, etc.)
  • Excellent written and verbal communication in English, effective with technical and business audiences
View full posting on CareerOneStop → ID: f2ee8858280e
Principal Data Scientist
Microsoft Corporation · Redmond, WA
Senior Doctorate
2026-05-06
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
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
Machine Learning Engineer III
Indeed · Portland, OR
Mid-level Doctorate
2026-05-06
Responsibilities
  • As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the team, and guide other members of the team to achieve product/technical goals. On a daily basis, you will explore data and formulate problem statements, develop and deploy predictive models while monitoring them in production, and guide the team on the same. Additionally, you will partner with cross-functional teams, evangelize your team's work, and stay updated with the latest advancements in the field.
  • Partner with cross-functional teams to enhance and optimize search algorithms for improved accuracy, relevance, and overall user experience.
  • Experiment with Proof of Concept Machine Learning model improvements, scale them to production, and run iterative A/B experiments to improve our matching technology while partnering with other teams
  • Define and clarify project priorities, deliverables, and success criteria in partnership with cross-functional teams.
  • Act as a bridge between technical and non-technical collaborators, facilitating effective communication and comprehension of project goals and outcomes.
  • Mentor and grow other software engineers and Machine Learning Engineers across teams
  • Break down larger Machine Learning initiatives into pieces that deliver incremental business value and guide the team through implementing them
  • Represent Indeed at major Machine Learning conferences, such as Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the International Conference on Learning Representations (ICLR).
  • *Skills/Competencies
  • Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master's degree with a minimum of 6 years of experience; or a PhD with 3 years experience
  • Prior success in deploying impactful Machine Learning solutions to large-scale production systems, while partnering across teams
  • Solid knowledge of data structures and algorithms
  • Sense of ownership and accountability as a key contributor in the technical and product domains
  • Knowledge and practical experience working on Deep Learning Libraries (like Torch, Tensorflow, etc.)
  • Excellent written and verbal communication in English, effective with technical and business audiences
View full posting on CareerOneStop → ID: ea05576560d7
Machine Learning Engineer, Firefly Services
Adobe Inc. · Seattle, WA
Mid-level Doctorate
2026-05-02
Requirements
  • MS or PhD in Computer Science, Machine Learning, or a related field-or equivalent industry experience.
  • 1-3+ years of experience in machine learning, including production-scale deployments.
  • 1-3+ years of experience leading large-scale, GPU-intensive GenAI systems (training, inference, and optimization).
  • Experience with GenAI frameworks and tools such asPyTorch, CUDA, Triton, TensorRT,Nvidia Dynamo, and Python.
  • Good understanding of generative model architectures, includingdiffusion models, transformers, and GANs.
  • Good communication and leadership skills, with a track record of driving alignment in matrixed organizations.
Preferred
  • Experience withmodel serving, inference, orchestration, and GPU resource managementin large-scale environments.
  • Hands-on expertise inKubernetes, distributed systems, and MLOps platforms.
Responsibilities
  • Adobe Firefly'sGenerative AI Servicesteam is seekingSeniorMachine Learning Engineersfor our GenAI Services area. In this high-impact role, you will work with a team of talented engineers in building scalable, high-performance generative AI systems-powering features across Adobe products like Firefly, Photoshop, Illustrator, Express, Stock, and Premiere.You will design and develop efficient inference pipelines, optimize models for latency and through at inference, and build APIs and ecosystems that integrate both Adobe's first-party and third-party generative models into Adobe suite of products that serve individual and enterprise customers. You will tackle Adobe's most complex engineering challenges at the forefront of the the industry, set technical direction, and mentor other ML engineers.Job Responsibilities
  • Design and evelopmentof core GenAI services and APIs that integrate a wide range of generative models into Adobe's flagship products.
  • Design and buildML workflows for enterprise-scale model customization, serving, and ecosystem integration.
  • Collaboratewith Adobe Research and other model developer teams with a focus on model inference strategies and productization of those model
  • Build and optimizeGPU-accelerated pipelines for both (customized) model training and inference-prioritizing performance, scalability, and reliability.
  • Foster a culture of innovation, technical excellence, and continuous improvement across the organization.
View full posting on CareerOneStop → ID: 0948b122b9a9
Staff Machine Learning Engineer, Search & Knowledge Platform
Apple · Seattle, WA
Senior Doctorate
2026-05-01
Requirements
  • MS in Computer Science or related field
  • 10+ years of work experience in machine learning, deep learning or related field
  • 10+ years experience in shipping Search and Q&A technologies and ML systems
  • Excellent programming skills in mainstream programming languages such as C++, Python, Scala, and Go
  • Experience delivering tooling and frameworks to evaluate individual components and end-to-end quality
  • Strong analytical skills to systematically identify opportunities to improve search relevance and answer accuracy
  • Strong written and verbal communication with the ability to articulate complex topics
  • Excellent interpersonal skills and teamwork; demonstrated ability to connect and collaborate with others
  • Passion for building phenomenal products and curiosity to learn
Preferred
  • PhD in Computer Science, Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or related field
  • Strong industry background and experience in search and related technologies (LLMs, Machine Learning, NLP, Information Retrieval, Question Answering)
  • Strong and validated experience of ML development and production systems
  • Experience working with foundation models and LLMs
Responsibilities
  • Apple is where individual imaginations come together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us strengthening each other's ideas. That happens because every one of us believes that we can make something wonderful and share it with the world, changing lives for the better! Here, you'll do more than join something - you'll add something.
  • The Information Intelligence team is redefining how billions of people use their devices to get information. We are an Applied ML team pushing the limits of question answering, assistant response ranking, and search technologies, while also responsible for a production service. We are part of a wider effort to power information across a variety of Apple products - including Siri, Spotlight, Safari, Messages, Lookup, and more.
  • As a Staff Machine Learning Engineer, you play a critical role in developing world-class Search and Q&A experiences for Apple customers with cutting-edge search technologies and large language models.
  • As a member of our fast-paced group, you'll have the unique and rewarding opportunity to shape upcoming products from Apple. Our team includes a diversity of backgrounds from applied scientists with a focus in NLP to experienced distributed systems engineers. As such, we are looking for candidates with in-depth understanding of machine learning fundamentals, applied machine learning experience, and strong software engineering skills.
  • Our team is responsible for delivering next-generation Search and Question Answering systems across Apple products including Siri, Safari, Spotlight, and more. This is your chance to shape how people get information by leveraging your Search and applied machine learning expertise along with robust software engineering skills. You will collaborate with outstanding Search and AI engineers on large scale machine learning to improve Query Understanding, Retrieval, and Ranking, developing fundamental building blocks needed for AI powered experiences such as fine-tuning and reinforcement learning. This involves pushing the boundaries on document retrieval and ranking, developing sophisticated machine learning models, using embeddings and deep learning to understand the quality of matches. It also includes online learning to react quickly to change and natural language processing to understand queries. You will work with petabytes of data and combine information from multiple structured and unstructured sources to provide the best results and accurate answers to satisfy users' information-seeking needs.
  • As part of our team, you will be leveraging and improving upon the latest deep learning techniques, such as LLM and RAG, in order to understand queries and user intents, rank documents, and find useful answers to users' questions. Our team is responsible for training, fine-tuning and deploying these models at scale, using the latest advances for online inference optimization. Following is the primary list of responsibilities for an ML engineer in the team:
View full posting on CareerOneStop → ID: 964d5769cf12
Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible)
Capital One · Olympia, WA
Manager Doctorate
2026-05-01
Requirements
  • Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
  • A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 years of experience performing data analytics
  • A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 5 years of experience performing data analytics
  • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
  • At least 2 years of experience leveraging open source programming languages for large scale data analysis
  • At least 2 years of experience working with machine learning
  • At least 2 years of experience utilizing relational databases
Preferred
  • Ph.D. in Physics, Computer Science, Mathematics, or a related field with a strong focus on quantum information or quantum computing.
  • At least 7 years of experience in quantum computing research and development.
  • At least 7 years of experience partnering with quantum hardware developers to implement and evaluate algorithms.
  • At least 7 years of experience in quantum algorithms (e.g. Shor's algorithm, Grover's algorithm, Variational Quantum Eigensolver (VQE), and Quantum Approximate Optimization Algorithm (QAOA)).
  • At least 7 years of experience in quantum information theory and quantum computing applied to Machine Learning.
  • Excellent verbal and written communication skills with the ability to effectively communicate technical advances and strategy to research scientists, engineering teams, senior executives, and non-technical audiences.
  • Knowledge of advanced quantum hardware and their associated control systems.
  • Experience with large-scale classical simulation of quantum systems (e.g., with tensor networks or state-vector simulators).
  • Experience with production-level quantum hardware or cloud-based quantum services.
  • Worked with datasets or systems involving 100+ qubits.
  • Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
  • Capital One is open to hiring a Remote Employee for this opportunity.
  • The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
  • Remote (Regardless of Location): $209,000 - $238,500 for Sr Mgr, Data Science
  • McLean, VA: $229,900 - $262,400 for Sr Mgr, Data Science
  • Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
  • This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
  • Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website (https://www.capitalonecareers.com/benefits) . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
  • This role is expected to accept applications for a minimum of 5 business days.
View full posting on CareerOneStop → ID: 9ee44c336ec7
Sr. Director, Machine Learning Engineering (Remote-Eligible)
Capital One · Olympia, WA
Director Doctorate
2026-05-01
Requirements
  • Bachelor's degree in Computer Science, Engineering, or AI plus at least 10 years of experience developing or leading AI and ML algorithms or technologies, or Master's degree plus at least 8 years of experience developing or leading AI and ML algorithms or technologies
  • At least 5 years of people leadership experience
Preferred
  • 7 years of experience managing and leading an engineering team
  • 8+ years of experience deploying scalable, responsible AI solutions on major cloud platforms (AWS, GCP, Azure)
  • Master's or PhD in Computer Science or a relevant technical fieldProven expertise designing, implementing, and scaling personalization platforms and recommendation systems across feed personalization, ads ranking, or targeted marketing messaging
  • Proficiency in Python, Java, C++, or Golang; hands-on experience with ML frameworks (PyTorch, TensorFlow) and orchestration tools (Databricks, Airflow, Kubeflow)
  • Experience optimizing large-scale training and inference systems for hardware utilization, latency, throughput, and cost
  • Deep expertise in cloud-native engineering, containerization (Docker, Kubernetes), and automated CI/CD deploymentDeep experience with MLOps, model observability, and production ML lifecycle management
  • Strong track record building organizations, developing managers and senior engineers, and leading through scale and ambiguityExcellent communication and presentation skills, with the ability to influence senior stakeholders and articulate complex AI concepts clearly
  • Proven leadership in driving platform strategy, cross-functional execution, and technical direction across a large organization
  • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers
  • *_Capital One will consider sponsoring a new qualified applicant for employment authorization for this position._
  • The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
  • Remote (Regardless of Location): $286,200 - $326,700 for Sr. Dir, Machine Learning Engineering
  • McLean, VA: $314,800 - $359,300 for Sr. Dir, Machine Learning Engineering
  • Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
  • This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
  • Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website (https://www.capitalonecareers.com/benefits) . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
  • This role is expected to accept applications for a minimum of 5 business days.
Responsibilities
  • Lead and scale a high-performing engineering organization responsible for the Personalization Platform that powers real-time, personalized product experiences and multi-channel targeted user messaging across Capital One products and services.
  • Define the technical strategy, delivery roadmap, and operating model for a portfolio spanning recommendation systems, ranking, decisioning, GenAI infrastructure, MLOps, and low-latency application-serving systems
  • Build, develop, and manage engineers and engineering leaders; set a high bar for hiring, performance, talent density, coaching, and succession planning across the organization
  • Partner cross-functionally with Product, Data Science, Cloud Infrastructure, and Machine Learning Platform teams to align strategy, prioritize investments, and co-develop advanced recommendation systems and algorithms serving Capital One users
  • Drive the design, buildout, and operation of robust ML infrastructure and pipelines supporting feature extraction, model training, testing, guardrails, evaluation, deployment, and both real-time and batch inference with strong reliability, scalability, and operational rigo
  • Architect low-latency, event-driven systems for real-time personalization and decisioning based on streaming data, user behavior, and contextual signals
  • Drive the evolution of MLOps practices through automated, metrics-backed deployment workflows, validation and testing systems, model lifecycle governance, and scalable observability
  • Guide the adoption of state-of-the-art AI and LLM optimization techniques to improve scalability, cost, latency, throughput, and reliability of large-scale production AI systems
  • Provide organizational technical and people leadership by influencing architecture, engineering standards, delivery excellence, incident management, and cross-team strategy while mentoring managers, tech leads, and senior engineers.
  • Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
  • Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI.
  • Capital One is open to hiring a Remote Employee for this opportunity.
View full posting on CareerOneStop → ID: 2898be3b6034
Sr. Distinguished Machine Learning Engineer (Remote-Eligible)
Capital One · Olympia, WA
Senior Doctorate
2026-05-01
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
Senior Data Scientist - AI Services and Platforms
Highmark Health · Olympia, WA
Senior Doctorate
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 Data Scientist - Product
Snowflake Inc. · Clyde Hill, WA
Senior Doctorate
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
Machine Learning Scientist - Personalization Science, Apple Media Products
Apple · Seattle, WA
Mid-level Doctorate
2026-04-28
Requirements
  • 6+ years of relevant work experience.
  • Deep knowledge of machine learning powered personalization algorithms, design patterns and tools. In particular, this includes deep learning, reinforcement learning and unsupervised learning methods.
  • Knowledge of generative artificial intelligence applied to recommendation systems.
  • Practical real-world experience with building scalable recommendation systems.
  • Proven grasp of the open-source Python ML/AI tech stack, including Tensorflow, pytorch, scikit-learn, numpy-scipy-pandas.
  • Technical competence in production-quality software development.
  • Familiarity with big data technologies.
  • Strong written & oral communication skills.
  • Master's in a quantitative field, including Computer Science, Maths, Statistics, Physics, etc.
Preferred
  • PhD in a quantitative field, including Computer Science, Maths, Statistics, Physics, etc.
Responsibilities
  • Wonder how Apple's Media Products show relevant search results and recommendations across Apple's media offerings - including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books? Come join us! Research, design and develop machine learning models that personalize the App Store for billions of users worldwide! Propose, prototype and evaluate algorithm improvements. Build large-scale personalized recommender systems for Apple Music, Apps & Games Recommendations, Video, Podcast and Books Recommendations. See your work touch the lives of billions of Apple users worldwide.
  • The Apple Services Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books. And we do it on a massive scale, meeting Apple's high expectations with high performance, to deliver a huge variety of entertainment in over 35 languages to more than 150 countries. Our scientists and engineers build secure, end-to-end solutions powered by machine learning. Thanks to Apple's unique integration of hardware, software, and services, designers, scientists and engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, flexible, and multi-functional, offering greater exposure to the array of opportunities here.
  • We are looking for a world-class researcher to help us solve challenging problems in personalization science using the latest advances in machine learning. With your expertise, we want to develop novel solutions to power personalized experiences across the App Store that enrich the lives of our customers. You will have the incredible opportunity to see your solutions deployed at Apple's truly incredible global scale.
View full posting on CareerOneStop → ID: 9dc66a3f353b
Senior Machine Learning Engineer - Earner Incentive
Uber · Seattle, WA
Senior Doctorate
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
Staff Machine Learning Engineer - Rider Intelligence
Uber · Seattle, WA
Senior Doctorate
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 Director, AI/ML Engineering - Remote
UnitedHealth Group · Seattle, WA
Director Doctorate
2026-04-27
Requirements
  • Master's degree in Machine Learning, Artificial Intelligence, Computer Science, or a related field
  • 15+ years of experience in AI/ML with demonstrable career progression from individual contributor to technical leadership roles
  • Hands-on experience with machine learning libraries and frameworks
  • Current and extensive hands-on experience with modern AI tools, frameworks, and methodologies
  • Experience with data analysis tools and techniques
  • Experience implementing machine learning fairness and bias mitigation techniques
  • Public cloud experience (Azure, and/or GCP, and/or AWS)
  • Comprehensive knowledge of statistical methods, machine learning algorithms, and AI principles
  • Proven track record of hands-on development and implementation of enterprise-scale AI SaaS solutions with measurable business impact
  • Demonstrated ability to balance strategic leadership with hands-on technical contribution
  • Demonstrated solid and current programming skills in Python or other relevant programming languages
  • Proven ability to build and scale AI infrastructure and operations
Preferred
  • PhD or Master's degree in Machine Learning, Artificial Intelligence, Computer Science, or a related field
  • Active practitioner with current, deep technical expertise in AI technologies and applications; Natural Language Processing (NLP) and/or Large Language Models (LLM)
  • Healthcare experience and FinTech solutions
  • Proven exceptional leadership, communication, and executive presence skills
  • All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy
  • Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $159,300 to $273,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.
  • *Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
  • _At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission._
Responsibilities
  • Develop and execute org-wide AI strategy and roadmap aligned with business objectives and growth initiatives
  • Maintain hands-on involvement in key AI projects, actively contributing to code, model development, and technical solutions
  • Drive innovation through research and adoption of cutting-edge AI technologies and methodologies
  • Establish AI governance frameworks, ethical guidelines, and best practices across the organization
  • Personally design, develop, and implement AI and machine learning models using statistical analysis and deep learning algorithms
  • Collaborate with cross-functional leadership to translate business needs into AI strategy
  • Collaborate with team leads in the deployment and maintenance of AI models in production environments, ensuring scalability, reliability, and cost-effectiveness
  • Spearhead integration of AI solutions with existing systems and applications
  • Establish KPIs and performance metrics for AI solutions and drive continuous improvement
  • Present AI vision, roadmaps, and results to executive leadership and board members
  • Lead research initiatives and partnerships to maintain competitive advantage in AI capabilities
  • Mentor, develop, and retain top AI talent while building a culture of innovation
  • You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
View full posting on CareerOneStop → ID: 8be85cfaac66
Senior Machine Learning Engineer| Uber Direct
Uber · Seattle, WA
Senior Doctorate
2026-04-26
Requirements
  • Bachelor's degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related technical field, or equivalent practical experience.
  • 5+ years of experience building and shipping production-grade machine learning systems.
  • Strong proficiency in Python , plus experience with at least one additional programming language (e.g., Go, Java, C++, Scala).
  • Hands-on experience with modern ML frameworks such as PyTorch, TensorFlow, JAX, or Scikit-Learn .
  • Demonstrated experience deploying, monitoring, and maintaining ML models in production environments.
  • Solid understanding of statistics, feature engineering, model evaluation methodologies, and experimental design.
  • Strong software engineering fundamentals, including data structures, algorithms, and system design.
Preferred
  • Master's or PhD in Machine Learning, Computer Science, Statistics, or related field.
  • Experience building large-scale ML systems in a high-throughput, low-latency production environment.
  • Background in logistics, marketplace systems, forecasting, optimization, recommendation systems, or time-series modeling.
  • Experience with distributed data processing frameworks (e.g., Spark, Hive) and streaming systems (e.g., Kafka).
  • Familiarity with MLOps tooling such as Airflow, Kubeflow, MLflow, feature stores, and CI/CD pipelines for ML workflows.
  • Experience with A/B testing, experimentation frameworks, and causal inference.
  • Proven ability to optimize ML systems for scalability, reliability, observability, and latency.
  • Experience mentoring engineers and contributing to technical strategy.
  • *Success Attributes
  • *Machine Learning Depth: Strong foundation in ML theory and applied modeling, with the ability to balance trade-offs between accuracy, interpretability, and system performance.
  • *Engineering Excellence: Ability to design and implement scalable, maintainable ML systems that operate reliably in production.
  • *Ownership Mindset: End-to-end accountability for model quality, system health, and business impact.
  • *Cross-Functional Leadership: Ability to influence and collaborate effectively with Product, Science, and Engineering stakeholders.
  • *Impact Orientation: Focus on delivering measurable improvements to core business metrics through data-driven solutions.
  • *Why Uber Direct?
  • At Uber Direct, you'll help shape the future of logistics through data-driven intelligence at global scale. Your work will directly power the technology behind enterprise delivery and impact millions of customers worldwide. Join a team where experimentation, innovation, and ownership are core to our engineering culture.
  • For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.
Responsibilities
  • Uber Direct powers fast, reliable delivery for enterprise retailers and local businesses by leveraging Uber's world-class logistics network. As a Senior Machine Learning Engineer on the Uber Direct team, you will define and build intelligent systems that improve operational efficiency, customer experience, and predictive capabilities in real-time logistics at global scale.
  • You'll partner closely with Product, Data Science, and Engineering teams to design, deploy, and continually enhance machine learning-driven solutions that power core decision-making across the delivery lifecycle. Your work will directly influence key marketplace and logistics metrics across millions of global deliveries.
  • Develop High-Impact ML Solutions: Design, build, and productionize machine learning models that solve critical logistics problems such as ETA prediction, demand forecasting, dispatch optimization, anomaly detection, and delivery quality improvements.
  • Own the End-to-End ML Lifecycle: Lead projects from problem definition and data exploration through feature engineering, model development, evaluation, deployment, monitoring, and iteration.
  • Build Scalable ML Systems: Develop robust data pipelines, feature stores, training workflows, and model serving infrastructure that support both real-time and batch inference at scale.
  • Drive Business Impact: Define success metrics, run experiments, and rigorously evaluate model performance to ensure measurable improvements to KPIs such as Completion Rate, On-Time Rate, and Defect Rate.
  • Collaborate Cross-Functionally: Work closely with Product Managers, Data Scientists, Operations, and Backend Engineers to translate business problems into scalable ML solutions.
  • Technical Leadership & Mentorship: Provide technical direction, establish best practices in ML and MLOps, and mentor engineers across the team.
View full posting on CareerOneStop → ID: 2bebef2a2733
Data Scientist II - AI Assurance Researcher
Pacific Northwest National Laboratory · Seattle, WA
Mid-level Doctorate
2026-04-25
Requirements
  • BS/BA and 2 years of relevant experience -OR-
  • U.S. Citizenship
  • Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
  • As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
  • For foreign national candidates:
  • If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
  • Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
  • *Rockstar Rewards
Preferred
  • Degree in computer science, engineering, mathematics, or a related field.
  • Familiarity with the current ML research landscape, particularly in explainable AI, adversarial machine learning, AI safety, and the science of deep learning.
  • Hands-on experience analyzing the internal structures of deep learning models, particularly large language models and large vision models.
  • Proficiency in PyTorch and associated deep learning libraries.
  • Experience designing and executing experiments on HPC systems.
  • Experience in translating research prototypes into deployable tools and capabilities.
  • Demonstrated strong communication and collaboration skills, with the ability to work effectively in a multi-disciplinary team environment.
Responsibilities
  • PNNL is seeking a Data Scientist II - AI Assurance Researcher who has experience in understanding, exploring, and manipulating the internal mechanics and behaviors of AI models and can provide valuable insights into the decision boundaries and mathematical fingerprints of data properties. The selected candidate should have extensive experience training models, accessing and working with data embeddings, the ability to derive theoretical queries from empirical results, and demonstrate the capacity to translate research papers and findings into mission relevant insights and tools.
  • Designs and executes rigorous ML experiments following community best practices, including large-scale training and evaluation on HPC infrastructure.
  • Evaluates AI systems across multiple dimensions, including standard performance metrics, generalization, robustness, and out-of-distribution behavior.
  • Analyzes the internal structures and representations of deep learning models, with emphasis on large language models and large vision models.
  • Assesses empirical results to identify trends, inform research direction, and recommend next steps.
  • Writes high-quality, well-documented research code that supports reproducibility and collaboration.
  • Contributes to publications and technical reports that communicate findings to both internal and external audiences.
  • Collaborates with senior researchers, engineers, and cross-functional teams to integrate research into broader systems and workflows.
  • Conducts work in secure environments with adherence to operational security requirements.
  • *This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.
View full posting on CareerOneStop → ID: 8fb806ff29bc
Data Scientist, Labs, SCOT Forecasting and Labs
Amazon · Bellevue, WA
Mid-level Doctorate
2026-04-25
Requirements
  • 3+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of data scientist experience
  • Bachelor's degree
Preferred
  • Master's degree, or PhD
  • Natural curiosity and desire to learn
Responsibilities
  • Partner with customer teams to design rigorous large-scale experiments (such as randomized controlled trials and quasi-experiments) to evaluate policy updates and model improvements across millions of products, hundreds of fulfillment nodes, and diverse business contexts
  • Lead the end-to-end experimentation lifecycle, from hypothesis formulation through analysis and stakeholder alignment, to inform production rollout decisions
  • Advance causal inference methodology for supply chain settings, including treatment effect estimation, interference modeling, and emulation techniques that accelerate policy evaluation
  • Build and maintain production-grade experimentation infrastructure and analytical tools using Python, SQL, Scala, and related technologies
  • Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform experimental design and policy development
  • Develop and scale supply chain emulation systems that model inventory dynamics end to end, enabling rapid offline evaluation of policy changes across millions of products without the cost and latency of live experiments
  • Translate complex research findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
  • Contribute to Amazon's scientific community and the broader research field through collaboration and publication in top-tier venues
  • You might start the morning reviewing results from a randomized controlled trial running across millions of products, digging into causal estimates and designing the next iteration. Later, you could be designing an experiment with a partner team where interference is unavoidable: treated and control units share fulfillment networks and inventory pools, and you need a credible strategy despite the spillover effects.
  • You'll build supply chain emulation systems that replicate inventory dynamics end to end, write code in Python, Scala, and SQL at a scale most scientists never encounter, and collaborate with scientists, engineers, and business teams across SCOT. Your research has a real chance of being published at top venues.
  • The work is hard, the problems are unsolved, and the impact is immediate. If you want to do research that ships, this is where you do it.
View full posting on CareerOneStop → ID: c5de427b9901
Data Scientist, Labs, SCOT Forecasting and Labs
Amazon · Bellevue, WA
Mid-level Doctorate
2026-04-25
Requirements
  • 3+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of data scientist experience
  • Bachelor's degree
Preferred
  • Master's degree, or PhD
  • Natural curiosity and desire to learn
Responsibilities
  • Partner with customer teams to design rigorous large-scale experiments (such as randomized controlled trials and quasi-experiments) to evaluate policy updates and model improvements across millions of products, hundreds of fulfillment nodes, and diverse business contexts
  • Lead the end-to-end experimentation lifecycle, from hypothesis formulation through analysis and stakeholder alignment, to inform production rollout decisions
  • Advance causal inference methodology for supply chain settings, including treatment effect estimation, interference modeling, and emulation techniques that accelerate policy evaluation
  • Build and maintain production-grade experimentation infrastructure and analytical tools using Python, SQL, Scala, and related technologies
  • Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform experimental design and policy development
  • Develop and scale supply chain emulation systems that model inventory dynamics end to end, enabling rapid offline evaluation of policy changes across millions of products without the cost and latency of live experiments
  • Translate complex research findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
  • Contribute to Amazon's scientific community and the broader research field through collaboration and publication in top-tier venues
  • You might start the morning reviewing results from a randomized controlled trial running across millions of products, digging into causal estimates and designing the next iteration. Later, you could be designing an experiment with a partner team where interference is unavoidable: treated and control units share fulfillment networks and inventory pools, and you need a credible strategy despite the spillover effects.
  • You'll build supply chain emulation systems that replicate inventory dynamics end to end, write code in Python, Scala, and SQL at a scale most scientists never encounter, and collaborate with scientists, engineers, and business teams across SCOT. Your research has a real chance of being published at top venues.
  • The work is hard, the problems are unsolved, and the impact is immediate. If you want to do research that ships, this is where you do it.
View full posting on CareerOneStop → ID: 32120793dbf4
Lead Data Scientist IV - GEOINT
Pacific Northwest National Laboratory · Seattle, WA
Senior Doctorate
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
Senior Data Scientist III - GEOINT
Pacific Northwest National Laboratory · Seattle, WA
Senior Doctorate
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
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
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
Data Scientist II - AI Assurance Researcher
Pacific Northwest National Laboratory · Richland, WA
Mid-level Doctorate
2026-04-25
Requirements
  • BS/BA and 2 years of relevant experience -OR-
  • U.S. Citizenship
  • Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
  • As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
  • For foreign national candidates:
  • If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
  • Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
  • *Rockstar Rewards
Preferred
  • Degree in computer science, engineering, mathematics, or a related field.
  • Familiarity with the current ML research landscape, particularly in explainable AI, adversarial machine learning, AI safety, and the science of deep learning.
  • Hands-on experience analyzing the internal structures of deep learning models, particularly large language models and large vision models.
  • Proficiency in PyTorch and associated deep learning libraries.
  • Experience designing and executing experiments on HPC systems.
  • Experience in translating research prototypes into deployable tools and capabilities.
  • Demonstrated strong communication and collaboration skills, with the ability to work effectively in a multi-disciplinary team environment.
Responsibilities
  • PNNL is seeking a Data Scientist II - AI Assurance Researcher who has experience in understanding, exploring, and manipulating the internal mechanics and behaviors of AI models and can provide valuable insights into the decision boundaries and mathematical fingerprints of data properties. The selected candidate should have extensive experience training models, accessing and working with data embeddings, the ability to derive theoretical queries from empirical results, and demonstrate the capacity to translate research papers and findings into mission relevant insights and tools.
  • Designs and executes rigorous ML experiments following community best practices, including large-scale training and evaluation on HPC infrastructure.
  • Evaluates AI systems across multiple dimensions, including standard performance metrics, generalization, robustness, and out-of-distribution behavior.
  • Analyzes the internal structures and representations of deep learning models, with emphasis on large language models and large vision models.
  • Assesses empirical results to identify trends, inform research direction, and recommend next steps.
  • Writes high-quality, well-documented research code that supports reproducibility and collaboration.
  • Contributes to publications and technical reports that communicate findings to both internal and external audiences.
  • Collaborates with senior researchers, engineers, and cross-functional teams to integrate research into broader systems and workflows.
  • Conducts work in secure environments with adherence to operational security requirements.
  • *This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.
View full posting on CareerOneStop → ID: 0c61ba8edab7
Lead Data Scientist IV - GEOINT
Pacific Northwest National Laboratory · Richland, WA
Senior Doctorate
2026-04-25
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
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
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
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
(Fall 2026) Annapurna Labs at AWS Internship (US) - Machine Learning Systems & Silicon Innovation
Amazon · Seattle, WA
Intern Doctorate
2026-04-24
Requirements
  • Work 40 hours/week minimum and commit to 12 week internship maximum
  • Currently pursuing a BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related technical field
  • Must be enrolled in a full-time degree program at time of application and returning to school after the internship
  • Programming experience in C, C++, Python, or similar languages
  • Experience in two or more of the following areas: 1. Systems programming or low-level software development 2. Compiler design or optimization 3. Machine learning frameworks (PyTorch, JAX, TensorFlow) 4. Distributed systems or parallel computing 5. Performance analysis and optimization 6. Hardware design (RTL, Verilog, FPGA development)
Preferred
  • Previous internship, research, or project experience in hardware/software co-design, ML systems, or computer architecture
  • Contributions to open-source projects or research publications
  • Completed or currently enrolled in coursework covering machine learning, parallel computing, computer architecture and/or compiler construction
View full posting on CareerOneStop → ID: 4a08e5acb3e3
Sr. Machine Learning Engineer, Core Engineering
Pinterest, Inc. · Seattle, WA
Senior Doctorate
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
(USA) Senior Manager, Data Science
Walmart · Bellevue, WA
Manager Doctorate
2026-04-23
Requirements
  • Deep understanding of machine learning, statistical modeling, and data science techniques used for risk mitigation in e-commerce or marketplace environments.
  • Proven ability to build, deploy, and optimize complex data science models to identify and mitigate fraud, performance, and operational risks.
  • Proficiency in tools and languages such as Python, R, Spark, Scala , and machine learning frameworks (e.g., TensorFlow, PyTorch, XGBoost) to develop and deploy risk models.
  • Ability to understand the end-to-end risk management process, from data ingestion and feature engineering to model deployment and real-time decision making.
  • 5-8 years of experience in leading teams or projects related to data science, including mentoring junior data scientists and guiding technical teams toward best practices in model development and deployment.
  • Comfortable navigating complex and uncertain situations, making data-driven decisions to improve risk management strategies in a fast-evolving environment.
  • Strong ability to translate complex data science concepts into clear, actionable insights for non-technical stakeholders across the organization.
  • Understanding how data science and risk management intersect with broader business objectives and the ability to align risk strategies with organizational goals.
  • Option 1 : Bachelor's degree in Statistics, Computer Science, Data Science, Mathematics, or related field, with 5-8 years of hands-on experience in data science, machine learning, or risk management.
  • Option 2 : Master's degree in a related field (e.g., Data Science, Machine Learning, Statistics, Applied Mathematics) with at least 3-5 years of applied experience working on data-driven risk management or fraud prevention.
  • Option 3 : 8-10 years of direct experience in data science, machine learning, or applied risk management within an e-commerce or marketplace setting.
  • _Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications._
  • Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related field.
Preferred
  • Expertise in using advanced machine learning techniques such as deep learning, reinforcement learning, or anomaly detection for fraud detection or risk mitigation.
  • Experience with big data technologies like Apache Spark , Hadoop , and cloud-based data solutions (e.g., AWS, Google Cloud) to build scalable risk management platforms.
  • Proficiency in data manipulation and analysis tools such as Pandas, NumPy , and SQL for data wrangling, feature engineering, and analysis.
  • Strong background in model evaluation techniques including ROC/AUC, confusion matrices, precision/recall, and F1 scores, as well as experience with A/B testing and model validation
  • _Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications._
  • Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart's accessibility standards and guidelines for supporting an inclusive culture.
  • Masters: Business Administration, Masters: Information Systems, Masters: Statistics
  • *Primary Location...
  • 10900 Ne 4th St, Bellevue, WA 98004, United States of America
  • Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.
Responsibilities
  • The Senior Manager, DataScience will lead a team of data scientists to define, implement, test, and deploy decision strategies aimed at mitigating fraud and performance risks for Walmart Marketplace. In this role, you will work closely with cross-functional teams, including product, engineering, and data science, to continuously monitor, investigate, and respond to emerging risk trends. You'll be responsible for leveraging advanced data science methodologies to develop and refine risk management models, ensuring the strategies are effective and scalable across both domestic and international portfolios.
  • *How You'll Make an Impact:
  • Drive Data Science Innovation to protect the integrity of the Marketplace by applying advanced statistical methods, machine learning, and AI techniques to identify and mitigate fraud and performance risks.
  • Support Marketplace Growth by designing and implementing scalable, data-driven risk management solutions that align with key business objectives and growth targets.
  • Provide technical leadership and mentorship to your team, overseeing the development of decision models, managing model performance, and ensuring they are optimized for both accuracy and scalability.
  • Apply Advanced Data Science Techniques such as predictive modeling, supervised and unsupervised machine learning, deep learning, and anomaly detection to continuously improve risk strategies.
  • Collaborate Across Teams to integrate data science models with business processes, ensuring alignment between product, engineering, and data teams to address key risk areas effectively.
  • Monitor the performance of deployed models, identify opportunities for improvement, and iterate to enhance their predictive power and robustness in mitigating risks.
  • Develop Test & Measurement Frameworks to validate model effectiveness, utilizing rigorous A/B testing, statistical testing, and model evaluation to refine decision strategies.
  • Foster Innovation by exploring cutting-edge data science techniques, identifying opportunities to optimize decision-making, and driving improvements in risk management capabilities.
View full posting on CareerOneStop → ID: 4bb83fb26716
Staff Machine Learning Engineer - Cortex Code Quality
Snowflake Inc. · Bellevue, WA
Senior Doctorate
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
Requirements
  • Data Scientist Analyst -
  • Bachelor's Degree in Computer Science or Mathematics/Statistics and 2 or more years of experience in transforming data and developing insights for use in business decision area OR
  • High School Diploma or Equivalent in Computer Science or Mathematics/Statistics and 4 or more years of experience in transforming data and developing insights for use in business decision area OR
  • Zurich Certified Insurance Apprentice including an Associate Degree in Computer Science or Mathematics/Statistics and 2 or more years of experience in transforming data and developing insights for use in business decision area AND
  • Experience applying data transformation techniques such as exact and probabilistic matching methods; fuzzy matching, text mining, and data reduction
  • Sr Data Scientist Analyst -
  • High School Diploma or Equivalent with 7 or more years of experience in Computer Science, Statistics or Mathematics and experience transforming data in the business analysis area OR
  • Zurich Certified Insurance Apprentice including an Associate Degree in Computer Science, Statistics or Mathematics and 5 or more years of experience transforming data in the business analysis area OR
  • Bachelor's Degree in Computer Science, Statistics or Mathematics and 5 or more years of experience transforming data in the business analysis area OR
  • Master's Degree in Computer Science, Statistics or Mathematics and 3 or more years of experience transforming data in the business analysis area OR
  • PhD in Computer Science, Statistics or Mathematics and 0 or more years of experience transforming data in the business analysis area
Preferred
  • Possesses strong crop insurance knowledge and technical expertise
  • Understanding how MPCI (multi-peril crop insurance) products work and how they are priced
  • Experience with extracting data from relational databases
  • Advanced knowledge of statistical techniques and their application to business decisions
  • Ability to develop actionable solutions to business challenges
  • Advanced analytical and problem-solving skills
  • Strong verbal and communication skills
  • Your pay at Zurich is based on your role, location, skills, and experience. We follow local laws to ensure fair compensation. You may also be eligible for bonuses and merit increases. If your expectations are above the listed range, we still encourage you to apply-your unique background matters to us.
  • The combined salary range for this position is $87,200 - $188,700. The proposed salary range for the Data Scientist Analyst is $87,200 - $142,700, with short-term incentive bonus eligibility set at 10%.?The proposed salary range for the Sr Data Scientist Analyst is $115,200 - $188,700, with short-term incentive bonus eligibility set at 15%.
  • We offer competitive pay and comprehensive benefits for employees and their families. [Learn more about Total Rewards here .]
  • At Zurich, we value your ideas and experience. We offer growth, inclusion, and a supportive environment-so you can help shape the future of insurance. Zurich North America is a leader in risk management, with over 150 years of expertise and coverage across 25+ industries, including 90% of the Fortune 500®.
  • Join us for a brighter future-for yourself and our customers.
View full posting on CareerOneStop → ID: ee0fd960678e
Machine Learning Engineer, (Applied Machine Learning), AI & Data Platforms (AiDP)
Apple · Seattle, WA
Mid-level Doctorate
2026-04-22
Requirements
  • Bachelor of Science in Computer Science, Machine Learning, or a related quantitative field or equivalent experience
  • 2+ years of hands-on experience in applied AI/machine learning work in industry or 4+ years of hands on AI research and development experience in academia
  • Demonstrated expertise in generative AI, computer vision, natural language processing, or general machine learning with a passion for problem solving.
Preferred
  • MS or Phd in Machine Learning, Natural Language Processing, Computer Vision or related areas strongly preferred
  • Experience in ML frameworks for training, fine-tuning, and deploying ML/generative models at scale
  • Proven track record of building large scale, enterprise-grade ML/Gen-AI products in cloud environments (AWS, GCP , Azure) or on-prem infrastructure
Responsibilities
  • Imagine what you could do here. At Apple, revolutionary ideas have a way of becoming extraordinary products, services, and customer experiences. Join the Ai Data Platform Applied Machine Learning team to pioneer enterprise solutions where generative AI meets Apple's unique commitment to privacy-first innovation. Together, we'll create tools that redefine industries while safeguarding what matters most - our users' trust.
  • As a pivotal member of Apple's enterprise generative AI efforts, you will help design, build, and evolve models, tools and applications that power high-impact AI experiences across the company. You will contribute to the architecture and optimization of AI/gen AI systems built for high availability, scalability, and reliability, working across backend services and application layers. You would solve AI problems in gen AI Safety, machine translation, content understanding, multi-modality, multi-agent systems, fine tuning and more. Our team designs and implements SOTA AI Models, services, and AI platform components that advance adoption of gen AI at apple. We tackle unique AI challenges in AI Safety, privacy-preserving generations, efficient inference, and multimodal integration, while enabling teams to build on top of our foundations. We deliver production-grade systems and models that meet Apple's rigorous standards for quality, performance, and scalability.
View full posting on CareerOneStop → ID: 41a389766942
Senior Data Scientist
Fortive Corporation · Everett, WA
Senior Doctorate
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
Member of Technical Staff - Data Scientist
Microsoft Corporation · Redmond, WA
Senior Doctorate
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
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
Manager- Applied Sciences / Machine Learning
Microsoft Corporation · Redmond, WA
Manager Doctorate
2026-04-03
Requirements
  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
  • OR equivalent experience.
  • 3+ years of people management experience.
Preferred
  • Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
  • 8+ years of industry experience in software engineering and/or machine learning, with prior experience leading teams or technical leadership roles.
  • Solid hands-on background in machine learning, including LLMs, NLP, or recommendation systems.
  • Proven track record of delivering large-scale, production-grade ML systems.
  • Experience leading or owning critical projects in recommendation systems or AIGC scenarios.
  • Proficiency in programming languages such as C/C++, C#, Java, and/or Python.
  • Demonstrated experience managing and growing ML teams, including performance management and career development.
  • Solid expertise in deep learning frameworks such as TensorFlow or PyTorch.
  • Experience with LLM fine-tuning, evaluation, and real-world product deployment.
  • Experience leading projects through full product lifecycle, from concept to launch and iteration.
  • Background in distributed systems and large-scale data processing.
  • Solid foundation in data structures, algorithms, and system design.
  • Experience with large-scale data analytics tools such as Spark.
Responsibilities
  • Lead and grow a team of Applied Scientists and Machine Learning Engineers, including hiring, coaching, and developing talent across Applied Science and engineering.
  • Define technical vision and strategy for recommendation systems, Artificial Intelligence Generated Content (AIGC), and LLM-powered content generation.
  • Drive end-to-end execution across multiple initiatives, from ideation and design to production and iteration.
  • Oversee system architecture and scalability, ensuring robust, efficient, and high-quality ML solutions in production.
  • Partner cross-functionally with product, engineering, and leadership teams to align on priorities and deliver customer impact.
  • Champion innovation in AIGC applications, ranking, and recommendation algorithms.
  • Mentor and elevate the team, fostering a culture of technical excellence, collaboration, and continuous learning.
  • Communicate progress, insights, and strategy to senior leadership and stakeholders.
View full posting on CareerOneStop → ID: edd9ebd3d35f
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