About this role

Profile, optimize, and scale RL training runs to reduce iteration time
Integrate new optimization techniques as they emerge from the research community
Design and implement tools and environments that test the boundaries of model capabilities
Turn proof-of-concept ideas into robust training pipelines and best-in-class models

Strong Python and PyTorch proficiency, with hands-on experience optimizing training pipelines
Hands-on experience with reinforcement learning and the ability to translate optimization techniques from theory into practical implementations
Track record of integrating research ideas into robust, maintainable code
Experience with frameworks like DeepSpeed, FSDP, or vLLM for efficient model training and inference
Experience working with data pipelines, including curation, validation, and analysis to support post-training objectives
Contributions to open-source machine learning projects
M.S. or Ph.D. in Computer Science, Electrical Engineering, Mathematics, or a related field

The opportunity to work directly on state-of-the-art AI systems at one of the most advanced AI companies in the world
A fast-paced, collaborative environment where your work has direct impact on model performance and product capability
The satisfaction of knowing your craftsmanship helps define the next frontier in AI

Member of Technical Staff – Reinforcement Learning

Key skills