ML Infrastructure Engineer
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ML Infrastructure Engineer at SpaceXSI, Palo Alto, CA. Pay posted by the employer: $180k–440k/yr. Posted Jul 21, 2026, last seen on the employer's hiring page Nov 5, 2026.
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...
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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.
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Source: SpaceXSI on Greenhouse. FortHire is not the employer and doesn't take applications. Report a problem or request removal.