Senior Applied Scientist, Amazon Fulfillment Technology

Amazon•Bellevue, WA

19d

About The Position

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. 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

Requirements

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
Experience in building machine learning models for business application

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.