Applied Scientist, RL post-training, AWS

Amazon • Seattle, WA

2d • Onsite

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

• 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

Nice To Haves

• Experience with popular deep learning frameworks such as MxNet and Tensor Flow.
• First authored publications on the topic of LLM post-training in top-tier AI conferences such as Neurips, ICML, ACL, etc.

Responsibilities

• Develop innovative solutions to hard problems.
• Publish your findings at peer reviewed conferences and journals.
• LLM post-training to improve capabilities particularly for instruction following, reasoning over long context, and tool use, etc.

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
• sign-on payments
• restricted stock units (RSUs)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior