Pay
Higher than most similar jobs
$180K–$440K against $166K–$240K, the middle half of what similar US postings state.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
ML Infrastructure Engineer
Palo Alto, CA
Open 3 months, first seen by us 104 days ago- Pay
USD 180,000–440,000/yearAnnual period assumed — pay source
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.
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign, build, and scale GPU compute infrastructure and training frameworks
Develop data pipelines linking large-scale data, training, and inference systems
Work with ML teams to productionize models
Ensure scalability, reliability, and efficiency of large-scale ML systems
Mentor junior engineers
From the employer’s posting
Designing, building, and scaling GPU compute infrastructure, training frameworks, and experimentation tools
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
Mentoring junior engineers and contributing to the growth of the team
What you’ll bring
All qualificationsCore experience
- Bachelor's, master's, post-graduate, or Ph.D. degree in computer science, machine learning, or other quantitative discipline
- Deep familiarity with modern ML frameworks such as JAX or PyTorch
- Experience with job schedulers (e.g., Slurm), configuration management (Puppet/Ansible), or related infrastructure tooling
- 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
Qualification wording
Bachelor's, master's, post-graduate, or Ph.D. degree in computer science, machine learning, or other quantitative discipline
Deep familiarity with modern ML frameworks such as JAX or PyTorch
Experience with job schedulers (e.g., Slurm), configuration management (Puppet/Ansible), or related infrastructure tooling
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
Education & alternatives
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
Benefits in the posting
Full benefits wording- 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.
From the employer’s posting.
Posting record
Report an errorOpen 3 monthsWe first saw this posting 104 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 22, 2026104 days ago
- Recorded sightings
- 149
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 104
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,296 similar postings that came down. Coming down is not always a hire.
SpaceXSI is hiring
10 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring has slowed
- Its jobs tend to stay up a long time
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- C++
- Python
- Rust
- PyTorch
Where the posting names them
- 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:
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
Your next step
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
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.
- Location & working pattern
Palo Alto, CA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.