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Sr. ML Infrastructure Engineer

xAI is hiring a Sr. ML Infrastructure Engineer in Palo Alto, United States. It pays $180k-$330k a year and Level rates it ; you can apply on xAI.

Level's read on this job

  • Builds AI ●●●● is how Level rates this role: the job is building AI systems.
  • The posting mentions PyTorch and JAX among its tools and skills.
  • Level classes it as a senior role.
  • xAI has 304 other open roles on Level.

AI in this role

PyTorchJAX

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.

SR. 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
  • 5+ years of industry experience working with high traffic or large-scale production environments, distributed systems, GPU infrastructure, and/or deep learning applications
  • 5+ 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 - $330,000 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.

How we rate this

Sr. ML Infrastructure Engineer at xAI rates 98 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

PyTorchJAX

Questions you could be asked

  1. What's a project where you used PyTorch hands-on?
  2. Walk me through how you've used JAX in your day-to-day work.
  3. How would you decide a model or AI system is ready to ship?
  4. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: PyTorch and JAX. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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