About the role
- The RL infrastructure team is looking for an engineer to help with low precision RL training and inference
- 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
Benefits
- Health and wellness: Comprehensive health insurance including medical, dental, vision, and disability coverage
- Life and family: Life and AD&D insurance and fertility benefits to ensure our team’s well-being and peace of mind
- Flexible vacation: We work hard but avoid burn out. Take time off when you need it
- Visa sponsorship: We support international talent with visa sponsorship to join our team
- 401(k) plan: Retirement savings plan to secure your financial future
All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.
- Proficiency in programming languages such as Python, C++ and/or Rust; frameworks such as PyTorch, Jax, CUDA
- Experience in LLM inference
- Willingness to dive deep and solve hardcore problems at all levels of the stack
- Experience in building, debugging, and optimizing efficiency of large-scale distributed systems
- Strong knowledge in quantization and numerics in LLM inference and training
- Experience in developing inference engines, e.g. SGLang, vLLM
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