Applied Scientist, LLM

- Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals
- 1+ years of building machine learning models or developing algorithms for business application experience
- Experience in LLM finetuning, pretraining, testing, and prompt engineering.

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, WA, Seattle - 136,000.00 - 184,000.00 USD annually
Do you want to shape the next generation of AI-driven customer experiences for Amazon’s most ground-breaking products? Join us and help invent the future of shopping.

We are seeking a passionate, innovative, and highly skilled Applied Scientist with expertise in AI, Agentic LLMs, Generative AI, Machine Learning, and NLP to help build LLM-powered solutions for Amazon’s BuyForMe product, which enables Amazon customers to discover and purchase products from any merchants through browser use agents.

Our team develops science and agentic AI capabilities that power a seamless, end-to-end shopping experience for Amazon customers. We build and advance technologies such as web agent frameworks, LLM fine-tuning, reinforcement learning, context engineering, RAG, MCP, and automated benchmarking to improve pre-purchase, in-purchase, and post-purchase workflows.


Key job responsibilities
As an Applied Scientist on our team, you will:

Invent, implement, and evaluate state-of-the-art models and agentic systems that directly impact customer experience.

Conduct research that may lead to publications, patents, or cross-Amazon technical influence.

Collaborate with engineers, product managers, and other scientists to translate business challenges into scalable science solutions.

Run experiments with real customer data and validate hypotheses in a high-impact product environment.

Drive excellence in model performance, safety, reliability, and evaluation frameworks.