Jobs — Clinical Data Managers

AI and Data Science Engineer II Deloitte · Seattle, WA Mid-level Master's 2026-06-04

Requirements

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

Preferred

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

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2026-06-04

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

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2026-06-04

Business Intel Engineer I, Network Design Planning & Engineering (NDPE) Amazon · Bellevue, WA Entry-level Bachelor's 2026-06-04

Requirements

2+ years of data analysis using tools such as Excel, Pivot Tables, SQL, Tableau, or equivalent experience
Experience using BI tools (e.g., Tableau, Adobe) to visualize data
Experience with a variety of digital workflows
Experience defining requirements and using data and metrics to draw business insights

Preferred

Bachelor's degree or advanced studies in a quantitative field (engineering, economics, math, and statistics)
Knowledge of data warehousing and data modeling
Experience with various statistical techniques (regression analysis, coefficient correlation)

Responsibilities

Partner with teammates across product, science, and engineering to understand what questions the business needs answered - then design and deliver the data solutions to answer them.
Build and maintain interactive dashboards and visualizations that track how the transportation network is performing.
Create and manage the automated data workflows that feed reports and analytical tools, ensuring accuracy and reliability.
Conduct deep-dive analyses into operational performance, uncover root causes of issues, and recommend improvements backed by data.
Proactively look for ways to make existing reports and dashboards faster, more accurate, and easier to use.
Analyze historical trends to surface insights that support planning and forecasting decisions.
Respond to time-sensitive requests with clear, well-structured analysis.
As a Business Intelligence Engineer I, you'll support product, science, and engineering teams by building reports, dashboards, and data pipelines that help monitor and improve the performance of Amazon's outbound transportation network. Your day may include gathering requirements from stakeholders, developing SQL queries, validating data accuracy, and visualizing trends that inform operational decisions. You'll contribute to team goals by digging into data to answer key business questions, identifying anomalies, and sharing insights that support planning and forecasting efforts. With guidance from senior team members, you'll continue to grow your technical skills and business acumen in a collaborative, fast-paced environment.

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2026-06-04

Business Intelligence Engineer, Ad Sales Finance Analytics Amazon · Seattle, WA Mid-level 2026-06-04

Requirements

4+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
1+ years of SQL, ETL or Oracle experience
4+ years of processing large, multi-dimensional datasets from multiple sources experience
1+ years of performing statistical analysis experience
1+ years of developing automated reporting experience
Experience with data visualization using Tableau, Quicksight, or similar tools
Experience with data modeling, warehousing and building ETL pipelines
Experience in Statistical Analysis packages such as R, SAS and Matlab
Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

Preferred

Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

Responsibilities

Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions - Own the forecasting model for IX countries and enhance the existing model to align with sales calls while minimizing forecasting errors. - Make recommendations for new metrics, techniques, and strategies to improve team performance and measurement in the future - Define the data elements and data structure that our team should leverage to enable analytical and reporting capabilities for our business development team - Design and influence operational best practices for reporting and analytics to enable the team to scale - Prepare and deliver business reviews to the senior management team regarding progress and roadblocks - Work with engineering and the data warehouse to enable the appropriate capture and storage of key data points - Enable effective decision making by retrieving and aggregating data from multiple sources and compiling it into a digestible and actionable format - Participate in strategic & tactical planning discussions
Your day will be a dynamic blend of data exploration, strategic problem-solving, and cross-functional collaboration. You'll dive deep into complex data landscapes, crafting visualizations and models that reveal hidden patterns and opportunities for Amazon's advertising platforms.

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2026-06-04

Business Intelligence Engineer, AWS Regions Finance Amazon · Seattle, WA Mid-level Bachelor's 2026-06-04

Requirements

5+ years of SQL, ETL or Oracle experience
Experience with data visualization using Tableau, Quicksight, or similar tools
Bachelor's degree or equivalent in Finance, Business, Economics, Mathematics, or other highly quantitative fields
Experience with data modeling, warehousing and building ETL pipelines
Experience in Statistical Analysis packages such as R, SAS and Matlab
Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

Preferred

Experience working directly with business stakeholders to translate between data and business needs
Experience managing, analyzing and communicating results to senior leadership
Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

Responsibilities

Work with business customers to gather requirements and deliver complete data analytical solutions
Learn why customers are asking for data and what their underlying questions and business goals are
Own the design, development, and maintenance of ongoing metrics and analyses used to drive key business decisions
Recognize and adopt best practices, including data integrity, accuracy, and reliability, as well as documentation
Drive data democratization throughout the organization, enabling others to self-serve their data needs

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2026-06-04

Business Intelligence Engineer, Denied Party Screening Amazon · Seattle, WA Mid-level 2026-06-04

Requirements

5+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
Experience with data visualization using Tableau, Quicksight, or similar tools
Experience with data modeling, warehousing and building ETL pipelines
Experience in Statistical Analysis packages such as R, SAS and Matlab
Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

Preferred

Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

Responsibilities

Interface with business customers to gather requirements, drive reporting or analytic projects to help solve complex challenges.
Design, implement, and support datasets that provide structured data for reporting and analysis.
Develop reports and dashboards across various business teams to drive adoption and increase visibility into key measures of business performance.
Analyze billions of rows of data to find the root causes behind variances and drive business insights.
Investigate and implement new big data technologies to provide automatic resolutions to address business needs.
The successful candidate will demonstrate good business acumen, experience in developing reports and conducting analysis, strong technical skills and communication skills, an ability to work effectively cross functional teams, and an ability to work in an ever-changing environment.

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2026-06-04

Business Intelligence Engineer, Rapid & Rural Logistics (R2L) Science & AI Amazon · Bellevue, WA Mid-level 2026-06-04

Requirements

3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
1+ years of SQL, ETL or Oracle experience
1+ years of processing large, multi-dimensional datasets from multiple sources experience
1+ years of performing statistical analysis experience
1+ years of developing automated reporting experience
Experience with data visualization using Tableau, Quicksight, or similar tools
Experience with data modeling, warehousing and building ETL pipelines
Experience in Statistical Analysis packages such as R, SAS and Matlab
Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

Preferred

Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

Responsibilities

As a BIE II on our team, you will sit at the intersection of data, science, and product - owning end-to-end analytics solutions from ambiguous problem spaces to deployed insights. You'll design scalable data models, build high-quality datasets, and partner closely with Data Scientists and System Development Engineers to integrate predictive models and AI agents into business workflows. This role goes beyond dashboards: you'll share how AI is used in production, evaluate model performance, and ensure outputs are accurate, explainable, and actionable.
Key responsibilities include developing performant ETL pipelines, defining metrics and experimentation frameworks, and building intuitive reporting layers that surface both descriptive and predictive insights.
We're looking for someone who is equally comfortable writing complex SQL, thinking statistically about data, and collaborating on AI-driven solutions. If you're excited about building the next generation of data + AI agents/systems that directly impact operations, this role offers high ownership and visibility.

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2026-06-04

Business Intelligence Engineer, Tools & Automation, WW Engineering & Innovation Amazon · Bellevue, WA Mid-level 2026-06-04

Requirements

3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
1+ years of SQL, ETL or Oracle experience
1+ years of processing large, multi-dimensional datasets from multiple sources experience
1+ years of performing statistical analysis experience
1+ years of developing automated reporting experience
Experience with data visualization using Tableau, Quicksight, or similar tools
Experience with data modeling, warehousing and building ETL pipelines
Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

Preferred

Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

Responsibilities

Build and maintain dashboards, tools, and platforms that serve VP/SVP-level executives
Translate PM-defined requirements into scalable technical solutions
Design data architecture connecting leadership level team portfolios to org-level views
Own the full build lifecycle: requirements intake ? design ? build ? deploy ? iterate
Automate manual reporting processes currently done in Excel
Evaluate existing tools and build integrations or replacements
Maintain and iterate on all platforms post-launch based on PM feedback and evolving needs
Document technical architecture and create runbooks for platform maintenance

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2026-06-04

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)

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2026-06-04

Data Scientist I, Demand Forecasting Amazon · Bellevue, WA Entry-level Bachelor's 2026-06-04

Requirements

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

Preferred

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

Responsibilities

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

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2026-06-04

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!

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2026-06-04

Manager, Machine Learning Engineering - Ad Platforms The Walt Disney Company · Seattle, WA Manager Master's 2026-06-04

Requirements

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

Preferred

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

Responsibilities

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

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2026-06-04

Senior Machine Learning Engineering Manager, Ad Platforms The Walt Disney Company · Seattle, WA Manager Master's 2026-06-04

Requirements

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

Preferred

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

Responsibilities

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

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2026-06-04

Staff Machine Learning Engineer - News, Books, and Stocks Team Apple · Seattle, WA Senior Master's 2026-06-04

Requirements

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

Preferred

Experience in a technical leadership role.

Responsibilities

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

View posting →

2026-06-04

Associate, Marketing Business Intelligence Humana · Olympia, WA Entry-level Bachelor's 2026-06-04

Requirements

Bachelor's degree or higher in Information Systems, Data Analytics, related field, or equivalent related professional experience
2+ years of experience with Power BI and familiarity with DAX for creating calculated columns, measures, and custom logic within Power BI reports
Advanced experience with SQL and data modeling concepts
Proven ability to troubleshoot data pipeline issues and proactively identify and resolve data quality problems to ensure reliable, accurate, and timely reporting
Experience in data preparation tasks such as cleansing, validation, and transformation to support accurate reporting
Strong grasp of data governance principles, including documentation, version control, and meta data management

Preferred

Experience in healthcare or other regulated industries
Knowledge of HIPAA and data privacy standards
Exposure to marketing or operational reporting environments
Familiarity with Databricks, Snowflake
Experience with performance tracking and KPI development
*Additional Information
*Preferred Locations: Arlington, VA; Louisville, KY; Atlanta, GA; Boston, MA; Chicago, IL; New York, NY; Tampa, FL, Nashville, TN, Dallas, TX, Seattle, WA, Denver, CO, and Fort Lauderdale, FL. The associate selected for this role should anticipate periodic in-office work to support collaboration, key team meetings, and leadership engagement. _Remote options will be considered based on role needs and candidate experience_
To ensure Home or Hybrid Home/Office employees' ability to work effectively, the self-provided internet service of Home or Hybrid Home/Office employees must meet the following criteria:
At minimum, a download speed of 25 Mbps and an upload speed of 10 Mbps is recommended; wireless, wired cable or DSL connection is suggested
Satellite, cellular and microwave connection can be used only if approved by leadership
Employees who live and work from Home in the state of California, Illinois, Montana, or South Dakota will be provided a bi-weekly payment for their internet expense.
Humana will provide Home or Hybrid Home/Office employees with telephone equipment appropriate to meet the business requirements for their position/job.
Work from a dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information
Humana offers a variety of benefits to promote the best health and well-being of our employees and their families. We design competitive and flexible packages to give our employees a sense of financial security-both today and in the future, including:
Health benefits effective day 1
Paid time off, holidays, volunteer time and jury duty pay
Recognition pay
401(k) retirement savings plan with employer match
Tuition assistance
Scholarships for eligible dependents
Parental and caregiver leave
Employee charity matching program
Network Resource Groups (NRGs)
Career development opportunities
*Our Hiring Process
As part of our hiring process for this opportunity, we may contact you via text message and email to gather more information using a software platform called HireVue. HireVue Text, Scheduling and Video technologies allow you to interact with us at the time and location most convenient for you.
If you are selected to move forward from your application prescreen, you may receive correspondence inviting you to participate in a pre-recorded Voice, Text Messaging and/or Video interview. Your recorded interview will be reviewed and you will subsequently be informed if you will be moving forward to next round of interviews.
If you have additional questions regarding this role posting and are an Internal Candidate, please send them to the Ask A Recruiter persona by visiting go/Buzz and searching Ask A Recruiter! Please be sure to provide the requisition number so we may be able to research your request quicker.
Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required.

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2026-06-04

Business Intelligence & Sales Enablement Lead Humana · Olympia, WA Senior Master's 2026-06-04

Requirements

Bachelor's Degree
7+ years in Project Management, Process management or Business transformation.
5+ years in Sales Enablement, Sales Operations, Revenue operations and/or Go-To-Market functions.
CRM Proficiency: Advanced knowledge of CRM platforms like Salesforce, particularly Sales cloud environments.
CMS/LMS Knowledge: Familiarity with Content Management Systems (CMS) and Learning Management Systems (LMS)
Analytical Mindset: Proficient in interpreting sales metrics and data-driven storytelling.
Strategic Communication: Ability to translate complex product / process technicalities into clear, value-based sales messaging.
Experience utilizing analytic tools (i.e. PowerBI, Tabelau)
WAH requirements: Must have the ability to provide a high speed DSL or cable modem for a home office. Associates or contractors who live and work from home in the state of California will be provided payment for their internet expense.
A minimum standard speed for optimal performance of 25x10 (25mpbs download x 10mpbs upload) is required.
Satellite and Wireless Internet service is NOT allowed for this role.
A dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information

Responsibilities

*CRM Strategy & Optimization
Manage Sales Tools: Lead the optimization and implementations of CRM system (e.g., Salesforce) enhancements partnering with agile product delivery teams to identify sales automation tools to ensure seamless data flow, and serving as the primary business owner.
Maintain CRM Hygiene: Monitor and enforce standards for data entry, pipeline hygiene, and forecasting discipline within the CRM.
Generate Performance Analytics: Create dashboards and reports in the CRM to track critical KPIs like quota attainment, win rates, and time-to-productivity for new hires.
Improve Workflow Automation: Identify bottlenecks in the sales process and leverage CRM capabilities to automate routine tasks, saving time for frontline sellers.
*Content Management & Strategy
Manage Central Repository: Own and organize a centralized content repository (e.g., Highspot, Seismic, Showpad), ensuring all materials are current, tagged properly, and easily searchable.
Track System and Content Adoption: Analyze usage data to determine which assets drive the most engagement and revenue, then refine the content strategy based on these insights.
Lead vendor management and stewardship engagement with our enablement vendors to
Develop Sales Collateral: Partner with Marketing and Product teams to create and maintain high-impact materials utilizing key capabilities embedded within our enablement solutions.
Support Strategic Sales enablement activities as needed.
Attend key internal and external events as necessary, including our annual National Sales Conference and key market events.
Partner with leadership on key transformation activities as needed.
Position could Lead 1 or 2 associates.

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2026-06-04

Medicaid Business Intelligence Engineer Humana · Olympia, WA Mid-level Master's 2026-06-04

Requirements

2+ years of experience in Python or Pyspark
2+ years of experience in Jupyter Notebook environment
2+ years of experience in Databricks Platform
2+ years of experience in Microsoft PowerBI or other data visualization software
2+ years of experience working with Big Data and performing root cause analysis.
2+ years of experience in business ownership of data processes
In depth experience in Microsoft Office including Excel formulas, pivots, charts, graphs, etc.

Preferred

Experience in Managed Care
Experience in Medicaid
Experience in risk adjustment
Experience with data mining and predictive modeling techniques
Ability to use data to drive business outcomes and decisions
Advanced Degree in a quantitative discipline, such as Mathematics, Economics, Finance, Statistics, Computer Science, Engineering or related field
*Additional Information

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2026-06-04

Senior AI/ML Engineer - Future Sensing, Embodied AI General Motors · Olympia, WA Senior Bachelor's 2026-06-04

Preferred

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

Responsibilities

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

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2026-06-04

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.

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2026-06-04

Business Intelligence & Sales Enablement Lead Humana · Boise, ID Senior Master's 2026-06-04

Requirements

Bachelor's Degree
7+ years in Project Management, Process management or Business transformation.
5+ years in Sales Enablement, Sales Operations, Revenue operations and/or Go-To-Market functions.
CRM Proficiency: Advanced knowledge of CRM platforms like Salesforce, particularly Sales cloud environments.
CMS/LMS Knowledge: Familiarity with Content Management Systems (CMS) and Learning Management Systems (LMS)
Analytical Mindset: Proficient in interpreting sales metrics and data-driven storytelling.
Strategic Communication: Ability to translate complex product / process technicalities into clear, value-based sales messaging.
Experience utilizing analytic tools (i.e. PowerBI, Tabelau)
WAH requirements: Must have the ability to provide a high speed DSL or cable modem for a home office. Associates or contractors who live and work from home in the state of California will be provided payment for their internet expense.
A minimum standard speed for optimal performance of 25x10 (25mpbs download x 10mpbs upload) is required.
Satellite and Wireless Internet service is NOT allowed for this role.
A dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information

Responsibilities

*CRM Strategy & Optimization
Manage Sales Tools: Lead the optimization and implementations of CRM system (e.g., Salesforce) enhancements partnering with agile product delivery teams to identify sales automation tools to ensure seamless data flow, and serving as the primary business owner.
Maintain CRM Hygiene: Monitor and enforce standards for data entry, pipeline hygiene, and forecasting discipline within the CRM.
Generate Performance Analytics: Create dashboards and reports in the CRM to track critical KPIs like quota attainment, win rates, and time-to-productivity for new hires.
Improve Workflow Automation: Identify bottlenecks in the sales process and leverage CRM capabilities to automate routine tasks, saving time for frontline sellers.
*Content Management & Strategy
Manage Central Repository: Own and organize a centralized content repository (e.g., Highspot, Seismic, Showpad), ensuring all materials are current, tagged properly, and easily searchable.
Track System and Content Adoption: Analyze usage data to determine which assets drive the most engagement and revenue, then refine the content strategy based on these insights.
Lead vendor management and stewardship engagement with our enablement vendors to
Develop Sales Collateral: Partner with Marketing and Product teams to create and maintain high-impact materials utilizing key capabilities embedded within our enablement solutions.
Support Strategic Sales enablement activities as needed.
Attend key internal and external events as necessary, including our annual National Sales Conference and key market events.
Partner with leadership on key transformation activities as needed.
Position could Lead 1 or 2 associates.

View posting →

2026-06-04

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