Member of Technical Staff - RL Inference

xAI xAI · AI Frontier · Palo Alto, CA · Model

Engineer to optimize inference stack for RL workloads, analyze performance bottlenecks, and implement novel RL techniques. Requires experience in distributed systems, LLM inference, and programming languages like Python/C++/Rust with frameworks like PyTorch/Jax/CUDA. Preferred skills include quantization, numerics, and inference engines.

What you'd actually do

  1. Design and optimize our inference stack for all shapes of RL workloads at xAI, from small scale ablations to production training runs.
  2. Analyze, profile and address performance bottlenecks in large scale RL systems
  3. Work closely with the modelling team to efficiently implement novel RL techniques and algorithms

Skills

Required

  • building, debugging, and optimizing efficiency of large-scale distributed systems
  • LLM inference
  • Python
  • C++
  • Rust
  • PyTorch
  • Jax
  • CUDA

Nice to have

  • quantization and numerics in LLM inference and training
  • developing inference engines
  • SGLang
  • vLLM

What the JD emphasized

  • low precision RL training
  • LLM inference
  • large scale RL systems
  • quantization and numerics in LLM inference and training

Other signals

  • RL inference optimization
  • low precision RL training
  • large scale RL systems