About the role#
This internship focuses on the intersection of distributed systems, machine learning, and performance engineering. You will help scale the next generation of large AI models for Autopilot and Optimus. You will work alongside researchers and infrastructure engineers to improve training efficiency and shorten iteration cycles. This role requires working on-site in Palo Alto, California.
What you'll do#
- Optimize large-scale distributed training across thousands of GPUs.
- Improve training throughput, utilization, reliability, and scalability.
- Develop tools to identify bottlenecks in compute, networking, memory, and data pipelines.
- Design and implement performance optimizations across PyTorch, CUDA, communication libraries, and training frameworks.
- Partner with researchers to evaluate how infrastructure changes impact model quality, convergence, and metrics.
- Analyze training runs and build dashboards that connect system performance to model outcomes.
- Drive improvements in model scaling efficiency.
- Debug complex issues across software, hardware, networking, and machine learning systems.
- Build infrastructure that accelerates experimentation for researchers.
What you'll need#
- Strong software engineering fundamentals in Python and C++.
- Experience with distributed systems, high-performance computing, or large-scale infrastructure.
- Understanding of machine learning fundamentals, including optimization, training dynamics, and evaluation.
- Familiarity with PyTorch and modern deep learning frameworks.
- Ability to analyze performance bottlenecks using profiling and observability tools.
- Strong debugging and problem-solving skills.
- Excellent communication and collaboration skills.
- Currently pursuing a degree in Computer Science or a relevant field.
- Graduation date between December 2026 and December 2027.
Location & details#
- Location: Palo Alto, California.
- Term: Fall 2026 and Winter 2027.
- Modality: Full-time, on-site.
- Compensation: $100,000 to $150,000 plus benefits.
About Tesla
Tesla produces electric vehicles, battery storage systems, and solar energy products. Founded in 2003, the company operates six vertically integrated factories across three continents. It is headquartered in Austin, Texas, and employs over 10,000 people. The organization designs, manufactures, sells, and services its products internally.
How to get in at Tesla
Applying early at Tesla provides a distinct advantage because recruiters review candidates before the applicant pool becomes unmanageable. Intern Insider sends an instant alert the moment a role matching your target is published anywhere, so you apply among the first and get seen before the pile grows. Reaching out to the right people often yields better results than submitting to a general queue. Intern Insider surfaces the recruiters behind the company roles so you can contact them directly to ask about the position or a referral, which materially improves your response rates.
