Principal Site Reliability Engineer (Vehicle Engineering)
SpaceX is hiring a Principal Site Reliability Engineer (Vehicle Engineering). Level rates it ; you can apply on SpaceX.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include PyTorch and TensorFlow.
- Level classifies it as a lead role.
- Level lists 2,800+ other open roles at SpaceX.
- The role was posted in the last few days.
AI in this role
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 enabling human life on Mars.
PRINCIPAL SITE RELIABILITY ENGINEER (VEHICLE ENGINEERING)
SpaceX HPC is a shared compute platform used across the company — vehicle and structures simulation, machine learning, AI inference, and more. We support every program at SpaceX to design and operate the worlds most advanced rockets and satellites. This role exists to put a real Site Reliability Engineer operating model on these capabilities and accelerating the world class engineering at SpaceX: toil reduction, automation, observability, and a sustainable incident process.
We are looking for a Principal Site Reliability Engineer who wants to own everything from Linux machines and our Infrastructure as Code, storage, and user facing applications – the whole ecosystem as a product, not as a ticket queue. You do not need a prior HPC title. You do need production instincts — you have operated real infrastructure, you write code to delete toil, and you care about whether users can actually get work done, not just whether nodes ping. You’ll work alongside HPC systems engineers who design and commission clusters to help make them more reliable and provide world class services for world class engineers.
Aerospace experience is not required. We value engineers who treat teammates with fairness and respect, who are self-critical, and who will take ownership of hard production problems.
RESPONSIBILITIES:
- Participate in the team's on-call rotation; practice sustainable incident response and blameless postmortems
- Manage node lifecycle with infrastructure as code: OS images, firmware, configuration management, kernel and driver stack
- Build observability for both HPC administrators and end users — cluster, node, and storage health for operators, and job/workflow-level signal for the people running work on the platform
- Reduce toil with automation; split time between operating production systems and writing the software that makes that work smaller
- Sustainably manage resources, including compute and storage
- Lead capacity planning with users across the company: understand what they will need next, and turn that into a concrete picture of tomorrow's compute and storage
- Collaborate with HPC systems engineers and with engineers across all disciplines across the company on operable, maintainable infrastructure
BASIC QUALIFICATIONS:
- Bachelor's degree in computer science, engineering, math, or a scientific discipline; OR 2+ years of professional experience operating production infrastructure in lieu of a degree
- 8+ years of experience with Linux operating systems in production
- 8+ years of experience operating production infrastructure (servers, services, or networks), including monitoring, debugging, and repairing what you own
PREFERRED SKILLS AND EXPERIENCE:
- 8+ years of professional experience in SRE, DevOps, or production infrastructure engineering
- Experience with monitoring and alerting (Prometheus, Grafana, Nagios, or similar)
- Experience deploying and maintaining configuration management or infrastructure as code (Ansible, Puppet, Terraform, or similar)
- Experience writing scripts/code (eg. Python or similar languages) to automate common tasks
- Experience with containers (Docker, Podman, Singularity/Apptainer)
- Experience with Kubernetes administration for on-premise deployment
- Experience with distributed or high-performance storage (VAST or similar), including capacity, performance, and lifecycle management
- Familiarity with HPC clusters, schedulers (Slurm, PBS, LSF), or GPU compute — not required; we will teach this
- Familiarity with scientific computing (CFD, FEA) and/or ML training workloads (PyTorch, TensorFlow, CUDA) and/or AI inference workloads
- Good understanding of version control, testing, continuous integration, build, deployment and monitoring
- Ability to communicate clearly with users, peers, and vendors in both incident and design settings
- Comfortable working with mission-critical and sensitive systems, with a sense of urgency appropriate to the responsibilities
- Eligibility for access to classified material up to TS/SCI with polygraph
ADDITIONAL REQUIREMENTS:
- Must be able to participate in an on-call rotation
- Must be willing to work extended hours and weekends as needed for incidents, cluster bring-up, and time-critical failures
ITAR REQUIREMENTS:
- To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.
SpaceX is an Equal Opportunity Employer; employment with SpaceX is governed on the basis of merit, competence and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability or any other legally protected status.
Applicants wishing to view a copy of SpaceX’s Affirmative Action Plan for veterans and individuals with disabilities, or applicants requiring reasonable accommodation to the application/interview process should reach out to EEOCompliance@spacex.com.
How we rate this
Principal Site Reliability Engineer (Vehicle Engineering) at SpaceX rates 85 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.
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.
Prepare for this job
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Skills and AI tools this role asks for
Questions you could be asked
- What's a project where you used PyTorch hands-on?
- Walk me through how you've used TensorFlow in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- 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 TensorFlow. 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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