Internship, Software Compiler Engineer, AI Inference (Fall 2026 or Winter 2027)

What to Expect

Consider before submitting an application:

This position is expected to start August or September 2026 and continue through fall term (ending approximately December 2026) or continuing into Winter/Spring 2027 if available and there is an opportunity to do so. 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.

Tesla is building a fully vertical AI inference stack—from custom silicon through compilers and runtimes to production models—because the highest performance comes from co-designing software and hardware so that every circuit is used as effectively as possible. Elon has noted that AI is already superhuman at many things and that we are in the singularity; the systems that turn that capability into real-world autonomy and robotics will run on the inference stack you help build.

In this role you will work on the compiler and runtime that execute neural networks in millions of Tesla vehicles and Optimus. Production deployment and analysis of live models drive the team’s direction, so your work has immediate impact on latency, efficiency, and the ability to ship more complex models. With full control of the hardware and a co-designed MLIR-based architecture, the compiler can exploit features that conventional stacks never see—enabling aggressive optimization, simplification of software layers, and exact mapping of models to silicon. This is high-leverage systems work at the intersection of compilers, machine learning, and custom AI hardware.

What You’ll Do

• Take ownership of parts of the AI Inference stack (Export / Compiler / Runtime), flexible based on skills, interests, and team needs
• Collaborate closely with the AI team to guide design and development of neural networks for production deployment
• Collaborate with the Hardware team to understand current architecture and propose future improvements
• Develop algorithms that 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 a relevant field of study with an expected graduation day 2028 or earlier
• 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