Senior Applied Scientist, Frontier AI Assets
Sunnyvale, CAJob$192–260K/yrSeen todaySeen in employer's feed today
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At a glance
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Job overview
Amazon’s Foundational AI team seeks an Applied Scientist to advance generative AI technology with large language models. The role supports development of RL Gyms, evaluates their usefulness for frontier model advancement, and develops techniques to advance LLMs. It also contributes to foundational model development through applied research, using Amazon’s data sources and computing resources to accelerate progress.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
Description
The Foundational AI (FAI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs).
Key job responsibilities
As an Applied Scientist with the FAI team, you will support the development of RL Gyms, assess their usefulness for the frontier model advancement and build techniques to advance the state of the art with LLMs. You will support the foundational model development in an applied research role. Your work will directly impact our customers in the form of products and services that make use of GenAI technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in LLMs.
A day in the life
You start your morning reviewing experimental results from a model training run you kicked off the previous afternoon, analyzing metrics and refining your approach. By mid-morning, you are whiteboarding a new algorithmic design with engineering partners, working through system integration details. After lunch, you lead a science review where you present findings and gather feedback from peers. Later, you pair with a junior scientist to debug a data pipeline issue, turning it into a coaching moment. Your day wraps up drafting a section of a research paper capturing your team's latest results.
About the team
The FAI team has a mission to push the envelope in GenAI with LLMs, in order to provide the best-possible experience for our customers.
Basic Qualifications
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PhD, or Master's degree and 6+ years of applied research experience
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3+ years of building machine learning models for business application experience
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Experience programming in Java, C++, Python or related language
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Experience with neural deep learning methods and machine learning
Preferred Qualifications
- Experience with development of foundation models and their evaluation
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 - 192,200.00 - 260,000.00 USD annually
How this job compares
Set against the 1,086 open Applied Scientist jobs on Olive Jobs, counted November 10, 2026.
- Pay
- This posting$192–260K/yr
- California median$172–260K/yr178 salary ranges
- US median$158–264K/yr1,042 salary ranges
This range's midpoint, $226K, is close to the California median midpoint ($223K) — in the middle half of Applied Scientist salary ranges in California.
- Openings
- Olive Jobs lists 201 open Applied Scientist jobs in California and 1,086 across the US. 1% of them nationwide are listed as remote or flexible.
- Hiring the most in California
- Amazon (this employer)110 open
- Microsoft Corporation9 open
- SAP9 open
- Experience
- This posting asks for at least 6 years of experience; Applied Scientist postings that state a minimum ask for 5 years at the median (894 postings).
- Education
- 429 of the 1,086 open Applied Scientist jobs (40%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 10, 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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