xAIMember of Technical Staff - RL Training Framework
6d ago
USALeadpythonjaxrustc++
Develop and optimize reinforcement learning training framework and infrastructure.
Responsibilities
- The RL infrastructure team is looking for an engineer to help develop our RL training framework.
- Design and implement the systems backing all RL workloads at xAI, from small scale ablations to production training runs.
- Profile, debug, and optimize end-to-end training performance
- Improve scalability and observability of the RL stack
Requirements
- Experience building, debugging, and optimizing efficiency of large-scale distributed systems
- Comfortable diving into unfamiliar areas and solving problems at all levels of the stack
- Proficiency in Python, Jax, Rust, and/or C++
Nice to have
- Experience with large scale LLM training infrastructure
- Strong knowledge of reinforcement learning techniques
- Experience with RL numerics
Conditions
- $180,000 - $440,000 USD
- Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.
- xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice .
Other
- xAI’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.