ML Infrastructure Engineer

xAI is hiring an ML Infrastructure Engineer in Palo Alto, United States. It pays $180k-$440k a year and Level rates it ; you can apply on xAI.

Level's read on this job

On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
The posting mentions PyTorch, JAX and Python among its tools and skills.
Level classes it as a mid-level role.
xAI has 296 other open roles on Level.

AI in this role

Build and scale GPU compute infrastructure and training pipelines for large-scale machine learning.

pytorchjaxpythoncrustcuda

distributed-systemsgpu-infrastructuremlopsinfra

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.

ABOUT THE ROLE:

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, 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

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.

How we rate this

ML Infrastructure Engineer at xAI rates 90 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.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ 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.

Key facts

ML Infrastructure Engineer is an open job at xAI.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $180k-$440k a year.
The role is based in Palo Alto, CA.
The job was posted on July 22, 2026.
Seniority: mid.
Applications are handled by xAI. Apply on xAI

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Distributed SystemsGPU InfrastructureMLOpsInfraPyTorchJAXPythonC

Questions you could be asked

Tell me about a project where distributed systems was part of your work. What did you do?
Tell me about a project where gpu infrastructure was part of your work. What did you do?
Tell me about a project where mlops was part of your work. What did you do?
Tell me about a project where infra was part of your work. What did you do?
Walk me through how you've used PyTorch in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Distributed Systems, GPU Infrastructure, MLOps, Infra, and PyTorch. 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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