← All roles

ML Infrastructure Engineer

xAI· Engineering
Apply on company site
Hybrid (Palo Alto, CA)$180k - $440kfull-timePosted 3mo ago

About the role

Role focused on building and optimizing a high-performance ML platform to power recommendations on X, including GPU compute infrastructure, data pipelines, and collaboration with ML teams to productionize models.

Responsibilities

  • Designing, building, and scaling GPU compute infrastructure, training frameworks, and experimentation tools to enable rapid iteration on ML hypotheses
  • Developing data pipelines and integrating large-scale data, training, and inference systems
  • Collaborating with ML teams to productionize models and ensure seamless integration across the stack
  • Ensuring scalability, reliability, and efficiency of large-scale machine learning systems
  • Working across the full stack to solve complex problems independently
  • Mentoring junior engineers and contributing to the growth of the team

Qualifications

  • Bachelor, Master, Post-graduate or PhD in computer science, machine learning, or other quantitative discipline; or equivalent work experience
  • 2+ years of industry experience working with high traffic or large-scale production environments, distributed systems, GPU infrastructure, and/or deep learning applications
  • 2+ years experience with ML platforms, training infrastructure, or close collaboration with modeling engineers and data scientists
  • Strong proficiency with Python and experience with compiled languages such as C++ or Rust

Skills

Required:GPU infrastructurePythonC++ or Rust

Benefits

  • equity
  • comprehensive medical, vision, and dental coverage
  • access to a 401(k) retirement plan
  • short & long-term disability insurance
  • life insurance
  • various other discounts and perks
Last updated Oct 14, 2026. Interested? Apply on the company site.

About xAI

liquid-ai-recruiting-target

More open roles at xAI