ABOUT THE ROLE:The RL infrastructure team is looking for an engineer to help with low precision RL training and inference.
RESPONSIBILITIES:- Design and optimize our inference stack for all shapes of RL workloads at xAI, from small scale ablations to production training runs.
- Analyze, profile and address performance bottlenecks in large scale RL systems
- Work closely with the modelling team to efficiently implement novel RL techniques and algorithms
BASIC QUALIFICATIONS:- Experience in building, debugging, and optimizing efficiency of large-scale distributed systems
- Experience in LLM inference
- Proficiency in programming languages such as Python, C++ and/or Rust; frameworks such as PyTorch, Jax, CUDA
- Willingness to dive deep and solve hardcore problems at all levels of the stack
PREFERRED SKILLS AND EXPERIENCE:- Strong knowledge in quantization and numerics in LLM inference and training
- Experience in developing inference engines, e.g. SGLang, vLLM
