Member of Technical Staff, xAI

• Experience building, debugging, and optimizing large scale distributed training systems
• Experience building async RL training frameworks
• Experience in inference systems
• Proficiency in Python, Jax, or Rust
• Candidates are expected to be located near Palo Alto or open to relocation

Desirable

• The reasoning infrastructure team builds an end-to-end RL training framework to enable pretraining-scale RL
• Design and implement state-of-the-art distributed RL systems
• Profile, debug, and optimize system performance
• Software and algorithm co-design with researchers
• 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 engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates

• After submitting your application, the team reviews your CV and statement of exceptional work
• If your application passes this stage, you will be invited to a 15 minute interview (“phone interview”) during which a member of our team will ask some basic questions
• If you clear the initial phone interview, you will enter the main process, which consists of four technical interviews:
• Coding assessment in a language of your choice
• Researcher technical sessions (2): These sessions will be testing your ability to formulate, design and solve concrete problems in real world with LLM. It can be research or engineering, depending on background/experience
• Meet the Team: Present your past exceptional work and your vision with xAI to a small audience
• Our goal is to finish the main process within one week. All interviews will be conducted via Google Meet