Overview In this role you will advance reinforcement learning post-training for frontier LLMs to enhance customer-service AI. You will collaborate with cross-functional teams within AWS AI to turn research into scalable solutions, tackle real-world problems, and publish findings in peer-reviewed venues. You'll work on optimizing instruction following, long-context reasoning, and tool usage for LLMs. This is a high-impact, mission-driven opportunity to shape how AI powers cloud services.
Compensation / Benefits- health insurance (medical, dental, vision, prescription)
- RSUs
- sign-on payments
- 401(k) matching
- paid time off
- parantal leave
Responsibilities- Develop RL-based post-training methods for LLMs to improve capabilities
- Partner with technology and business teams to apply research to customer problems
- Publish findings at peer-reviewed conferences and journals
- Deliver innovative solutions and scalable approaches for real-world use cases
- Collaborate with world-class engineers to bring ideas to production
Key requirements- 3+ years of building models for business application
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience with patents or publications at top-tier venues
- Proficiency in Java, C++, or Python
- Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or HPC
- collaboration with cross-functional teams
- strong communication and presentation
- problem-solving and curiosity
- Java
- C++
- Python
