Skip to content
getdataengineeringjobs
Back to results

ML Infrastructure Engineer

Palo Alto, California, United States Mid Full-time Posted

Summary

Written in English from the original posting

SpaceXSI is hiring an ML Infrastructure Engineer in Palo Alto to build and optimize a high-performance ML platform supporting recommendations on X. The role involves scaling GPU compute infrastructure, training frameworks, experimentation tools, data pipelines, and production ML systems. Candidates are expected to have experience with large-scale production environments, ML platforms, Python, and compiled languages.

Job description

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.

SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.

ML INFRASTRUCTURE ENGINEER

As an ML Infrastructure Engineer, you will play a pivotal role in building and optimizing the reliable, high-performance ML platform that powers recommendations on X. We're looking for exceptional engineers who are passionate about our mission and have a strong desire to make a meaningful impact.

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

BASIC QUALIFICATIONS:

  • Bachelor's, master's, post-graduate, or Ph.D. degree in computer science, machine learning, or other quantitative discipline
  • 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
  • Experience with Python and compiled languages such as C++ or Rust

PREFERRED SKILLS AND EXPERIENCE:

  • Deep familiarity with modern ML frameworks such as JAX or PyTorch
  • Low-level understanding of compute systems, including distributed storage, NVIDIA drivers, CUDA toolkits, and networking
  • Comfortable with Linux systems and orchestration tools
  • Experience with job schedulers (e.g., Slurm), configuration management (Puppet/Ansible), or related infrastructure tooling

COMPENSATION AND BENEFITS:

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at SpaceXSI, 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.

SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

The weekly Digest

The week's most transparent data engineering jobs in your inbox once a week.

Once a week, a few new jobs that state their salary, location and stack, plus links to the rest. No open tracking; clicks are counted per issue, not per person. Unsubscribe with one click.

Similar jobs

US$180k–440k / year Apply