RL Inference
SpaceX Super Intelligence
Palo Alto, CA3h agovia LinkedIn
About the Role
The RL infrastructure team is looking for an engineer to help with low precision RL training and inference.
Key Responsibilities
- Design and optimize our inference stack for all shapes of RL workloads at SpaceXSI, 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.
Requirements & Tech Stack
- 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.