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Senior Applied Scientist, Amazon Fulfillment Technology
at Amazon
Mid LevelNo visa sponsorshipData Science/AI/ML
Posted 6 hours ago
No clicks
- Compensation
- $150,400 – $260,000 USD
- City
- Not specified
- Country
- United States
Currency: $ (USD)
Lead the development of agentic systems to assist operational decision making and orchestration within Amazon Fulfillment Technology. You will train LLMs using supervised fine-tuning, post-training, and reinforcement learning, leveraging multimodal models for agentic reasoning, coding, and analytics. You will lead research projects, mentor interns, and publish findings for external publication. Responsibilities include generating training and preference data, reward modeling and policy optimization, supervised fine-tuning on step-by-step trajectories, RL for LLMs, memory/state management, vector search, grounding with RAG, and developing evaluation metrics for decision quality.
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 Amazon’s 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: https://tinyurl.com/AFTOverview
- PhD, or Master's 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
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 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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/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 https://www.aboutamazon.com/workplace/employee-benefits. 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 Amazon’s 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: https://tinyurl.com/AFTOverview
Basic Qualifications
- 3+ years of building machine learning models for business application experience- PhD, or Master's 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
Preferred Qualifications
- Experience in building machine learning models for business applicationAmazon 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 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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
