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xAIxAIPalo Alto, CA

Member of Technical Staff

Engineer optimizing RL inference stack for workloads from ablations to production training. Requires experience with large-scale distributed systems, LLM inference, and proficiency in Python/C++/Rust with PyTorch/JAX/CUDA.

Salary not listed
On-site5+ YOEML Engineering

About the role

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.

Skills

PythonC++RustPyTorchJAXCUDALlm InferenceQuantizationDistributed SystemsSglangvLLM

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