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Principal Applied Scientist, Frontier AI Assets , Frontier AI Assets

Amazon

BELLEVUE, WAJob$199–269K/yrSeen 3 days agoSeen in employer's feed 3 days ago

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At a glance

Compensation
$199–269K/yr
Location
BELLEVUE, WA
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

The Frontier AI Assets team builds training and evaluation assets, reinforcement-learning gyms, and a certification platform for Amazon’s generative AI models. The Principal Applied Scientist will set technical direction for building, evaluating, and scaling these assets and tools, while leading experiments and scientific reviews. The role combines hands-on asset development with technical leadership, collaboration across teams, and mentorship of scientists and engineers.

Skills & qualifications

RequiredNice to have

Skills

JavaC++PythonMachine LearningDeep LearningNeural MethodsReinforcement LearningRL GymsLearning EnvironmentsAgentic Tool UseTechnical DirectionScientific LeadershipAutomated EvaluationQuality ControlVerification ToolingDistributed TrainingModern ML FrameworksAlgorithm Development

Qualifications

PhD in CS, EE, Math or RelatedMaster's With Applied Research Experience10+ Years Relevant WorkPeer-Reviewed Publications

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
401(k) Match
Paid Time Off
Parental Leave

Full job description

Description

The Frontier AI Assets (FAI) team is looking for a passionate, talented, and inventive Principal Applied Scientist with a strong deep learning and reinforcement learning background to build the training and evaluation assets that advance frontier Generative AI (GenAI) with Large Language Models (LLMs).

AI models become more capable largely because of the learning environments, the RL gyms, in which they are trained. FAI builds those gyms and the platform that certifies them, so that model training teams across Amazon can rely on high-quality, graded assets. As a Principal on this team, you will set the technical direction for how these gyms and the tooling around them are built, evaluated, and scaled.

Key job responsibilities

As a Principal Applied Scientist with FAI, you will:

•Set technical direction across data collection, sampling, and evaluation for RL gyms focused on agentic tool use across a range of real-world domains.

•Design and lead experiments that produce reliable, efficient signal on what drives model improvement.

•Build gym-building tooling and automated quality control that scale with demand.

•Advance the science of how gyms are evaluated and validated before they're used in model training.

•Act as a hands-on technical leader: produce exemplary, high-quality assets yourself, and audit and support more junior scientists and engineers.

•Partner closely with domain experts and cross-functional teams, turning real-world problems into challenging, high-value tasks.

•Lead scientific reviews, scrutinize experimental design and verification, probe assumptions, and align teams toward coherent strategies. Contribute to hiring, mentorship, and the development of other scientists.

About the team

The FAI team has the mission to push the envelope in GenAI with LLMs, in order to provide the best-possible experience for our customers. We build frontier training and evaluation assets, RL gyms and the certification platform behind them, that directly shape how Amazon's models are trained and improved. We value scientific depth, hands-on building, and turning research into measurable impact at scale.

Basic Qualifications

  • Experience programming in Java, C++, Python or related language

  • PhD in Computer Science, Electrical Engineering, Mathematics, or a related technical field; or Master's degree with significant additional applied research experience.

  • Strong hands-on experience building machine learning models and systems for real-world applications, with deep learning and neural methods.

  • Experience with reinforcement learning and/or building RL gyms, learning environments, or agentic tool-use systems.

  • Experience setting technical direction across data, modeling, and evaluation, and dealing with ambiguity and competing objectives.

  • Experience leading experienced scientists/engineers and developing more junior members.

Preferred Qualifications

  • 10+ years of relevant work in industry or academia experience

  • Experience building automated evaluation, quality-control, or verification tooling for training data or environments.

  • Experience with agentic tool use and improving the capabilities of LLMs (for example multi-step, tool-using agents).

  • Track record of creating novel algorithms and advancing the state of the art; peer-reviewed contributions in premier journals and conferences.

  • Experience with large-scale distributed training/compute and modern ML frameworks.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits .

USA, CA, Sunnyvale - 228,700.00 - 309,400.00 USD annually

USA, WA, Bellevue - 198,900.00 - 269,000.00 USD annually

How this job compares

Set against the 1,075 open Applied Scientist jobs on Olive Jobs, counted November 3, 2026.

Pay
  • This posting$199–269K/yr
  • Washington median$143–226K/yr242 salary ranges
  • US median$158–264K/yr1,036 salary ranges

This range's midpoint, $234K, is 19% above the Washington median midpoint ($197K) — in the top quarter of Applied Scientist salary ranges in Washington.

Openings
Olive Jobs lists 248 open Applied Scientist jobs in Washington and 1,075 across the US. Under 1% of them nationwide are listed as remote or flexible.
Hiring the most in Washington
Experience
Applied Scientist postings that state a minimum ask for 5 years of experience at the median; the middle half ask for 3 to 8 years (918 postings).
Education
582 of the 1,075 open Applied Scientist jobs (54%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 3, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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