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.

International Students: If your work authorization is through CPT, please consult your school on your ability to work 40 hours per week before applying. You must be able to work 40 hours per week on-site. Many students will be limited to part-time during the academic year. to experience life at Tesla by giving them ownership over projects that are critical to their team’s success.

In this role, you will be responsible for the internal working of the AI inference stack and compiler running neural networks in millions of Tesla vehicles and Optimus. You will collaborate closely with the AI Engineers and Hardware Engineers to understand the full inference stack and design the compiler to extract the maximum performance out of our hardware.

The inference stack development is purpose-driven: deployment and analysis of production models inform the team's direction, and the team's work immediately impacts performance and the ability to deploy more and more complex models. With a cutting-edge co-designed MLIR compiler and runtime architecture, and full control of the hardware, the compiler has access to traditionally unavailable features, that can be leveraged via novel compilation approaches to generate higher performance models.

What You'll Do

Take ownership of parts of AI Inference stack (Export/Compiler/Runtime) (flexible, based on skills/interests/needs)

Closely collaborate with AI team to guide them on the design and the development of Neural Networks into production

Collaborate with HW team to understand current HW architecture and propose future improvements

Develop algorithms to improve performance and reduce compiler overhead

Debug functional and performance issues on massively-parallel systems

Work on architecture-specific neural network optimization algorithms for high performance computing

What You'll Bring

Pursuing a degree in Computer Science, Computer Engineering, or relevant field of study with a graduation date between December 2026 - August 2027

Strong C++ programming skills and familiarity with Python

Solid understanding of machine learning concepts and fundamentals

Capable of delivering results with minimal oversight

Experience with quantization, MLIR, CUDA, and LLMs is a huge plus

Benefits
Compensation and 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.

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