Applied Scientist, RL post-training, AWS
About The Position
Do you want to work on Reinforcement Learning (RL) post-training of frontier Large Language Models (LLMs) to revolutionize customer service? Come join the world class researchers and academics in the AWS AI endeavor, and develop the science that powers countless new businesses in cloud computing! AWS, the world-leading provider of cloud services. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and journals. The scientific topics you are going to work on include, but are not limited to: LLM post-training to improve capabilities particularly for instruction following, reasoning over long context, and tool use, etc.
Requirements
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- 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
Nice To Haves
- Experience using Unix/Linux
- Experience in professional software development
Responsibilities
- Develop innovative solutions to hard problems.
- Publish your findings at peer reviewed conferences and journals.
Benefits
- health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
- 401(k) matching
- paid time off
- parental leave
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
