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# Applied Scientist - Agentic AI, Amazon Fulfillment Technology AI Science

- **Company:** Amazon.com, Inc.
- **Location:** Bellevue, WA, United States
- **Experience:** Experienced
- **Salary:** $142,800.0 - $193,200.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Business Software, C++ (Programming Language), Data Mining, Distributed Systems, Python (Programming Language), Parsing, Search Technologies, Software Engineering, Reinforcement Learning, High Performance Computing, Large Language Models, Multi-Agent Systems, Virtual Agents
- **Published:** September 18, 2026
- **Apply:** https://dejobs.org/x/x/3BC397070DC9436D9E0E3429F95BD937/job/

## About the Role

* PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
 * 3+ years of building models for business application experience
 * Experience programming in Java, C++, Python or related language
 * Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred Qualifications

 * Experience using Unix/Linux
 * Experience in professional software development

## Description

As an Applied Scientist in Amazon Fullfilment Technology, you will lead the development of agentic systems to assist with operational decision making and orchestration. You will work building full agentic systems leveraging multi-agent orchestration, tool use, memory, and action execution. You will train LLMs using a combination of rejection sampling approaches, SFT, continual post-training, and Reinforcement Learning (RL).

These systems are deployed to Amazon buildings, and you will also work on rigorous offline and online evaluations.

Your work will leverage the latest LLMs 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., * Generating training and preference data for specific use cases (reasoning trajectories, tool traces)

 * Reward modeling and policy optimization for LLMs: DPO, IPO, RLHF/RLAIF with PPO/GRPO, rejection sampling.
 * Supervised fine-tuning on step-by-step trajectories and tool-use traces
 * Verbal Reinforcement Learning and Continual Learning
 * 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


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