AI Hardware Infrastructure Intern

Job Description

Internship, Software Engineer, AI Hardware Infrastructure (Fall 2026) | Tesla

The Tone:
This is an internship at Tesla, located on-site. Tesla is at the forefront of innovation, continuously pushing the boundaries of technology, including advanced AI hardware. This role is within the AIHW Infra team and is crucial for supporting Tesla’s ongoing AI hardware initiatives by developing robust automation, infrastructure, and services. The intern will directly contribute to accelerating AI workloads and ensuring the stability and efficiency of high-performance computing systems, collaborating with design and HPC groups.

The TL;DR
• Role: Internship
• Type: Full-time
• Location: In-person, on-site
• Pay: $40.00 – $65.00 hourly
• Team: AIHW Infra team
• Mission: Develop automation, infrastructure, and services to support Tesla’s AI hardware initiatives and accelerate workloads.
• Tech Stack: Python, Linux

What You’ll Actually Do
• Develop: Create and enhance Python libraries designed to automate, monitor, measure, and troubleshoot complex workflows operating on critical AI hardware infrastructure.
• Build: Dedicate approximately 50% of your time to actively building robust automation and infrastructure solutions, primarily utilizing Python and other relevant programming languages.
• Maintain: Establish and upkeep essential tools for infrastructure management, automation, observability, and comprehensive reporting, thereby ensuring consistent system reliability and optimal performance.
• Collaborate: Work closely with AI HW design and High-Performance Computing (HPC) teams to effectively identify, debug, and ultimately resolve performance bottlenecks and intricate cluster issues.
• Support: Provide crucial assistance to internal users by efficiently triaging errors, methodically root-causing underlying issues, and delivering effective, maintainable solutions.
• Proactively Address: Anticipate and address potential infrastructure challenges to minimize user impact, while also enhancing the overall scalability and efficiency of AI hardware workloads.

The Must-Haves
• Background: Currently pursuing a degree in Computer Science, Physics, Computer Engineering, Mechatronics, or other related technical fields, with an anticipated graduation date falling between December 2026 and August 2027.
• Experience: Possess experience or demonstrate a strong interest in the areas of automation, observability, and the full lifecycle of infrastructure development and deployment.
• Skills: Exhibit strong proficiency in Python and a proven adaptability to quickly learn and apply new programming languages and frameworks. This includes extensive familiarity with Linux administration and its internal workings, along with the ability to collaborate effectively with diverse cross-functional teams to debug and optimize complex systems.