ML Infrastructure Engineer

xAI|22 Jul 2026

fulltimeonsite

Before you apply

Listed location: Palo Alto, CA

Work arrangement: onsite. A remote label does not confirm worldwide eligibility or visa sponsorship.

Read the employer’s description for qualifications, compensation and work eligibility. Confirm the position is still open on the application page.

Job description supplied by xAI; category and skill labels may be inferred. How our listings work · Report a problem

Job Description

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. 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 employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.

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 xAI, 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.

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

Skills mentioned

PythonPyTorchJAXCUDARustC++Distributed SystemsGPU

Frequently asked questions

Is the ML Infrastructure Engineer position at xAI remote?

The ML Infrastructure Engineer role at xAI does not have a confirmed remote arrangement in our data. Check the employer description for its work location.

What type of employment is the ML Infrastructure Engineer role?

xAI is hiring for a full-time ML Infrastructure Engineer position.

Which skills are mentioned for the ML Infrastructure Engineer job at xAI?

Detected skill labels include Python, PyTorch, JAX, CUDA, Rust, C++, Distributed Systems, GPU. Check the employer description to distinguish required skills from preferred experience.