SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. 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.

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 SpaceXAI, 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

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