Internship, AI Performance Engineer, Performance Optimization (Fall 2026)

Description:
Consider before submitting an application:
This position is expected to start August or September 2026 and continue through summer 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.
The Performance Optimization team takes research models and makes them run efficiently on Tesla's AI-ASICs, powering Autopilot and Optimus. This role sits at the intersection of AI research, compiler development, kernel optimization, and hardware design. You'll collaborate with AI researchers on novel quantization techniques, precision improvements, and non-standard architectures. You'll develop optimized kernels using our MLIR-based compiler stack to achieve real-time latency for self-driving and humanoid robots. You'll work directly with hardware teams to shape our next-generation AI and Dojo chips.

Responsibilities:
Implement, optimize, and profile highly performant kernels for inference and training on Tesla's AI and Dojo ASICs

Work on a variety of edge and datacenter workloads, from small encoders/decoders to distributed LLM inference

Work with hardware teams to shape the next generation of Tesla hardware, evaluating architectural tradeoffs and balancing performance with versatility

Research and implement state-of-the-art machine learning techniques to achieve high performance on our hardware

Collaborate with the compiler team on programmability and performance

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

Hands-on experience with kernel optimization, distributed systems, inference runtimes, or serving frameworks

Experience with LLMs, transformers, state space models, diffusion models, CNNs, and their performance characteristics

Familiarity with performance modeling and roofline analysis

Understanding of computer and GPU architecture, SIMD, multithreading, and/or other accelerators with vectorized instructions

Strong analytical and debugging skills

Ability to work across team boundaries with compiler, hardware, and ML teams

Bonus: contributions to ML serving frameworks, compilers, and frameworks (e.g. SGLang, LLVM, PyTorch, MLIR)

Compensation & 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
$100000.00 - $150000.00 + benefitsPay 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.