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Tesla Motors, Inc.

Site Reliability Engineer, HPC Infrastructure

Tesla Motors, Inc., Palo Alto, California, United States, 94306

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What to Expect Tesla's Supercomputing/AI infrastructure team works directly with the high-performance computing and machine learning infrastructure on which our ML algorithms run; this includes virtual simulations, Autopilot hardware & silicon design. With the rapidly-growing need for more data and optimized compute resources, cluster builds are getting larger and increasingly complex. Continued development/automation of deployment, monitoring, self‑healing and alerting processes is imperative to the success of our engineering groups. As the scope and impact of our Optimus, Full‑Self‑Driving (FSD) & Robotaxi efforts continue to scale, so does the value of this team and its work.

As a Site Reliability Engineer, you will be responsible for maintaining and improving our platform to ensure our Full‑Self‑Driving (FSD) & Optimus engineering teams have the necessary tools and resources to be productive. This includes managing/operating our AI infrastructure, monitoring compute/GPU/network metrics, Linux troubleshooting & performance tuning, and security. Your work will directly facilitate neural network training at scale & streamline FSD development.

What You'll Do

Support the AI/ML cluster infrastructure on GPU platforms, focusing on systems automation, configuration management and deployment at scale

Improve our monitoring & self‑healing pipelines, as well as security posture

Optimize our server, storage and network performance

Develop new tools in Python, Golang or Bash/Shell

Use Infrastructure as Code best practices

Participate in 24x7 on‑call rotation

What You'll Bring

Proficiency in Python, Golang and/or Bash

Proficiency with Linux fundamentals and performance optimizations

Experience with configuration management software (Ansible, etc.), systems monitoring & alerting (Prometheus, Grafana, Telegraf, Splunk, etc.)

Experience with containerization technologies such as Kubernetes

Experience with high‑throughput low‑latency networks, GPU‑based computing systems, and/or high‑performance storage systems is a plus

Experience with Slurm, LSF and storage management of parallel file systems is a plus

Bachelor's Degree in Computer Science, Computer Engineering, Electrical Engineering, Physics or proof of exceptional skills in related field

3+ years of additional equivalent experience or evidence of exceptional ability related to the position

Compensation and Benefits Along with competitive pay, as a full‑time Tesla employee, you are eligible for the following benefits at day 1 of hire:

Aetna PPO and HSA plans > 2 medical plan options with $0 payroll deduction

Family‑building, fertility, adoption and surrogacy benefits

Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution

Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Aetna medical plan with HSA

Healthcare and Dependent Care Flexible Spending Accounts (FSA)

401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits

Company paid Basic Life, AD&D, short‑term and long‑term disability insurance

Employee Assistance Program

Sick and Vacation time (Flex time for salary positions), and Paid Holidays

Back‑up childcare and parenting support resources

Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance

Weight Loss and Tobacco Cessation Programs

Tesla Babies program

Commuter benefits

Employee discounts and perks program

Expected Compensation $164,480 - $246,720/annual salary + cash and stock awards + benefits

Pay offered may vary depending on multiple individualized factors, including market location, job‑related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

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