Internship, Software Engineer, Model Architecture & Training Performance Co-Design, AI (Winter/Spring 2026)

Consider before submitting an application:

This position is expected to start around January 2026 and continue through the Winter/Spring term (approximately April 2026) or into Summer 2026 if available and there is an opportunity to do so. We ask for a minimum of 12 weeks, full-time 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.

As a Software Engineer Intern within the Autopilot AI Infrastructure team, you will co-design neural network architectures with modeling engineers towards the goal of maximizing training speed performance.

At the core of our autonomy capabilities are neural networks designed to drive our cars. These models are trained on some of the largest supercomputers in the world. Training these models as fast as possible is critical to our mission. The focus of this role is to explore the space of equally valid neural network architectures from the perspective of driving capability, but to find those that have better training speed properties.

• Co-design neural network architectures with ML Engineers with the goal of minimizing time-to-training-convergence and maximize model flop utilization
• Instrument, profile, and analyze endtoend training (data loader, input pipeline, kernels, comms) to identify architecture-driven training bottlenecks
• Redesign blocks (attention variants, convolutional stems, normalization, routing, feature fusion) for higher arithmetic intensity and better kernel efficiency
• Explore width/depth/receptive-field tradeoffs to match quality baselines with reduced step time or improved throughput per accelerator
• Prototype and evaluate operator fusions, layout changes, and mixed precision variants to raise achieved FLOP utilization
• Partner with kernel / systems engineers to surface architecture patterns that enable kernel fusion or memory reuse
• Run controlled ablations to ensure driving performance parity while improving timetotraining convergence

• Strong knowledge of Python and Linux
• Experience in one of the following: PyTorch, JAX, TensorFlow, or equivalent auto-differentiation framework
• Experience training modern neural networks for vision, language or multimodality
• Familiarity with the GPU programming model and kernel software stack (CUDA, HIP, or Triton)
• Knowledge of machine learning, computer vision, or neural networks
• Pursuing a degree in Computer Science, Computer Engineering, or relevant field of study with a graduation date between 2026-2027

As a full-time Tesla Intern, you will be eligible for:

• Aetna PPO and HSA plans > 2 medical 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
• Employee Assistance Program
• Sick time after 90 days of employment 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

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.