Internship, Software Engineer, Foundation Inference Infrastructure (Summer 2026)

Tesla Motors, Inc.
100,000 - 150,000 USD
paid holidays, flex time, 401(k)
United States, California, Palo Alto
Jan 06, 2026
What to Expect Consider before submitting an application: This position is expected to start May 2026 and continue through summer term (ending approximately August 2026 or later, if available). We ask for a minimum of 12 weeks, full-time (40 hours/week) and on-site, for most internships. Our internship program is for students who are actively enrolled in an academic program.Recent graduates seeking employment after graduation and not returning to school should apply for full-time positions, not internships. As a member of the Foundation Inference Infrastructure team, you will design & implement a diverse set of backend services and tools that power autonomy software and hardware development processes. The systems you build will have a large impact on autonomy, from accelerating chip design & Machine Learning workflows, compiler development, model validation, and evaluation & validation of the complete software-hardware stack. In this role, you'll bring top-notch software engineering skills and can contribute to our systems immediately. A strong candidate will be an excellent software generalist with passion for building scalable infrastructure and optimizing backend pipelines for ML inference workloads and hardware design automation. What You'll Do Design and implement backend services and tooling that handles iteration and batch processing of inference, simulation, and evaluation workloads Work closely with the other Autonomy teams to build foundational components as well as bridge missing pieces in ML compiler and runtime infrastructure while designing for scalability, reliability, security and high performance What You'll Bring Currently pursuing a degree in Computer Science, Physics, Computer Engineering, Mechatronics or related fields with a graduation date between December 2026- August 2027 Proficiency with Python & PyTorch Familiarity of managing hardware inference chips like TPUs and of optimizing machine learning inference workloads for low latency and scale Familiarity with Operating Systems concepts such as networking, processes, file systems and virtualization Familiarity with concurrency programming Familiarity with C++ and / or Golang Experience with Linux, container orchestrator like Kubernetes or similar and bare metal setup tools like Ansible or similar Experience with data stores like PostgreSQL and Redis Strong problem-solving mindset with the ability to navigate ambiguous requirements and break down complex technical challenges into actionable solutions Self-directed learning approach; comfortable diving into unfamiliar codebases, technologies, and problem domains to quickly become productive Compensation and Benefits Benefits As a full-time Tesla Intern, you will be eligible for: Medical plans > plan options with $0 payroll deduction Family-building, fertility, adoption and surrogacy benefits Dental (including orthodontic coverage) and vision plans. Both have an option with a $0 payroll contribution Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Medical Plan with HSA Healthcare and Dependent Care Flexible Spending Accounts (FSA) 401(k), Employee Stock Purchase Plans, and other financial benefits Company Paid Basic Life, AD&D, and short-term disability insurance (90 day waiting period) 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 Commuter benefits Employee discounts and perks program Expected Compensation $100,000 - $150,000/annual salary + 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.