Senior Applied Scientist, Amazon Fulfillment Technology
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Job Location:
Bellevue, WA - USA
Yearly Salary:
$ 150400 - 260000
Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
As a Senior Applied Scientist in Amazon Fullfilment Technology you will lead the development of agentic systems to assist with operational decision making and orchestration. You will train LLMs using a combination of SFT post-training and Reinforcement Learning (RL).
Your work will leverage the latest LLMs and multimodal models to develop capabilities for agentic reasoning coding and analytics. You will also lead research projects to tackle unsolved problems mentor interns and author academic papers to summarize your findings for external publication.
Key job responsibilities
- Generating training and preference data for specific use cases (reasoning trajectories tool traces)
- Reward modeling and policy optimization for LLMs: DPO IPO KTO RLHF/RLAIF with PPO/GRPO KL control rejection sampling.
- Supervised fine-tuning on step-by-step trajectories and tool-use traces
- RL for LLMs Offline RL and off-policy evaluation
- Agentic memory/state management; episodic and semantic memory; vector search; grounding with RAG.
- Evaluation: developing decision quality metrics scaling LLM-based evaluations.
About the team
Amazon Fulfillment Technologies (AFT) powers Amazons global fulfillment network. We invent and deliver software hardware and data science solutions that orchestrate processes robots machines and people. We harmonize the physical and virtual world so Amazon customers can get what they want when they want it. Learn more about AFT: 3 years of building machine learning models for business application experience
- PhD or Masters 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
- Experience in building machine learning models for business application
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150400/year in our lowest geographic market up to $260000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity sign-on payments and other forms of compensation may be provided as part of a total compensation package in addition to a full range of medical financial and/or other benefits. For more information please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.
Your work will leverage the latest LLMs and multimodal models to develop capabilities for agentic reasoning coding and analytics. You will also lead research projects to tackle unsolved problems mentor interns and author academic papers to summarize your findings for external publication.
Key job responsibilities
- Generating training and preference data for specific use cases (reasoning trajectories tool traces)
- Reward modeling and policy optimization for LLMs: DPO IPO KTO RLHF/RLAIF with PPO/GRPO KL control rejection sampling.
- Supervised fine-tuning on step-by-step trajectories and tool-use traces
- RL for LLMs Offline RL and off-policy evaluation
- Agentic memory/state management; episodic and semantic memory; vector search; grounding with RAG.
- Evaluation: developing decision quality metrics scaling LLM-based evaluations.
About the team
Amazon Fulfillment Technologies (AFT) powers Amazons global fulfillment network. We invent and deliver software hardware and data science solutions that orchestrate processes robots machines and people. We harmonize the physical and virtual world so Amazon customers can get what they want when they want it. Learn more about AFT: 3 years of building machine learning models for business application experience
- PhD or Masters 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
- Experience in building machine learning models for business application
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150400/year in our lowest geographic market up to $260000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity sign-on payments and other forms of compensation may be provided as part of a total compensation package in addition to a full range of medical financial and/or other benefits. For more information please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.
Required Experience:
Senior IC
Key Skills
- Laboratory Experience
- Mammalian Cell Culture
- Biochemistry
- Assays
- Protein Purification
- Research Experience
- Next Generation Sequencing
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Flow Cytometry
About Company
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