Applied Scientist (RL Post-Training, AI)

TL;DR

Applied Scientist (RL Post-Training): Work on Reinforcement Learning post-training of frontier Large Language Models to improve instruction following, long-context reasoning, and tool use with an accent on revolutionizing customer service applications. Focus on developing innovative solutions to hard problems, partnering with teams on real-world challenges, and publishing findings at peer-reviewed conferences.

USA, WA, Seattle

Salary: 167,100 - 226,100 USD annually

Company

AWS, the world’s most comprehensive and broadly adopted cloud platform powering businesses from startups to Global 500 companies.

What you will do

• Develop RL post-training techniques for LLMs targeting instruction following, reasoning over long contexts, tool use, and related capabilities.
• Partner with technology and business teams to apply research to real-world customer problems in cloud computing.
• Leverage vast data and computational resources to innovate and prototype solutions.
• Publish research findings at top-tier AI conferences and journals.
• Collaborate with world-class engineers to bring ideas into production.

Requirements

• PhD or Master's degree + 6+ years of applied research experience
• Programming experience in Java, C++, Python, or related languages
• Experience with neural deep learning methods and machine learning

Nice to have

• Experience with deep learning frameworks like MxNet and TensorFlow
• First-authored publications on LLM post-training at NeurIPS, ICML, ACL, etc.

Culture & Benefits

• Inclusive culture with employee-led affinity groups, CORE, and AmazeCon events
• Work-life harmony with flexibility and support for personal sacrifices
• Mentorship, knowledge-sharing, and career growth resources
• Comprehensive benefits: health insurance (medical, dental, vision), 401(k) matching, paid time off, parental leave, Flexible Spending Accounts
• Sign-on payments and RSUs as part of compensation package