Internship, AI Hardware Silicon Validation Engineer, AI Hardware; Fall

What to Expect

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 of12 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 Internship Recruiting Team is driven by the passion to recognize and develop emerging talent. Our year-round program places the best students in positions where they will grow technically, professionally, and personally through their experience working closely with their Manager, Mentor, and team. We are dedicated to providing an experience that allows the intern to experience life at Tesla by including them in projects that are critical to their team's success.

The Tesla AI Hardware team is at the forefront of revolutionizing artificial intelligence through cutting-edge hardware innovation. Comprising brilliant engineers and visionaries, the team designs and develops advanced AI inference chips tailored to accelerate Tesla's machine learning capabilities. A key part of this effort is Dojo, Tesla's custom supercomputer system built to efficiently train massive neural networks on vast video data from the fleet.

The work of Tesla's AI Hardware team powers the neural networks behind Full Self-Driving (FSD), and Tesla humanoid robot, Optimus, pushing the boundaries of computational efficiency and performance. By creating custom silicon and optimized architectures, the team ensures Tesla remains a leader in AI-driven automotive and energy solutions, shaping a future where intelligent machines enhance human life.

The role will focus on developing Post-Silicon validation plan, tools, and infrastructure for Tesla's custom SoCs and Platforms designs. As a Silicon Validation Engineer, the candidate will take on challenges like validating High-Speed Serdes, perform system level power characterization, and troubleshooting complex hardware bugs and field returns. The candidate will regularly take part in hardware design and schematics review, firmware development, and building automated test infrastructures for running large volume of post silicon system level tests.

The candidate will also possess good system-level and architectural knowledge and some experience with DFT and PDE work.

• Create and execute synthetic workloads that stress the various functional blocks inside the silicon platforms such as the NPU, CPU, Camera Interface, etc.
• Assist in identifying and fixing any hardware bugs before going into production
• Bring up and characterize Autopilot Custom Silicon and PCBA
• Collaborate with diverse teams in hardware design, schematic reviews, firmware development, and building automated test infrastructures
• Write test plans, develop test cases, and catch design bugs before production
• Characterize and improve power and performance consumption at a system level
• Perform Failure Analysis on Factory and field return units

• Currently pursuing a degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field within a graduation date between 2026 - 2027
• Deep knowledge of computer architecture
• Microcontroller & Embedded Systems Programming Experience in C/C++
• Python and bash scripting
• Familiarity with git and version control systems
• Design, verification or validation disciplines, system/platform level debug and root cause isolation, methodology and tools
• Experience with Test Automation Framework Development
• Familiarity with Logic or Protocol Analyzer equipment
• Familiarity with ARM and /or x86 microarchitecture
• Familiarity with JTAG and/or OpenOCD