Jobs at Tesla

Internship, Software Engineer, AI Inference (Summer 2026)

at Tesla • Internship

Location

in-office (Palo Alto, United States)

Duration

3 months

Compensation

$150k/year

About this Opportunity

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.

Our team puts ML models into production- we train and deploy large neural networks for efficient inference on compute-constrained edge devices (CPU / GPU / AI ASIC). The nature of this role is multi-disciplinary - you will work at the intersection of machine learning and systems by building the ML frameworks and infrastructure that enable the seamless training, deployment, and inference of all neural networks that run at Tesla AI. The goal of the role is two-fold; to experiment with novel architectures under constrained compute and build the infrastructure to deploy such architectures.  

What You’ll Do

  • Build robust AI frameworks to lower neural networks to edge devices 

  • Build robust AI infrastructure to train and fine-tune networks for Tesla AI 

  • Deploy state-of-the-art neural networks on Tesla’s in-house AI ASIC, with an aim to maximize network performance while minimizing latency 

  • Collaborate with AI scientists and compiler engineers to effectively compress large models to run in low precision 

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 

  • Proficiency with Python, C/C++ is a nice to have but not required 

  • Proficiency with PyTorch or another machine learning framework 

  • Proficiency with training and deploying neural networks for real-world AI 

  • Proficiency with computer systems and computer architecture 

  • Experience with CUDA 

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

$100000.00 - $150000.00 + 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.

Tesla is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to any factor, including veteran status and disability status, protected by applicable federal, state or local laws.

Tesla is also committed to working with and providing reasonable accommodations to individuals with disabilities. Please let your recruiter know if you need an accommodation at any point during the interview process.


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