Internship

Job Description

Consider before submitting an application:  

This position is expected to start around August or September 2025 and continue through the Fall term (ending approximately December 2025) or continuing into Winter/Spring 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 member of the Dojo Machine Learning team, you will be responsible for enabling Tesla's neural networks to train efficiently on our upcoming in-house custom silicon supercomputer systems. Join a small team of experienced developers in optimizing and scaling the deployment of our Pytorch derived neural networks on Tesla's custom massively parallel Dojo accelerators. Work with many of the same great engineers who delivered Tesla's custom FSD Computer. The ideal candidate has experience with writing software for large distributed systems.

Job Responsibilities

• Understand and model the end-to-end training performance of the Autopilot Software team's Pytorch-derived neural networks on the Dojo system 

• Develop software that scales and improves training performance based on your analysis of the bottlenecks 

• Collaborate with the Dojo HW team to understand current HW architecture and propose future improvements 

Job Requirements

• Pursuing a degree in Computer Science, Computer Engineering, or relevant field of study with a graduation date between December 2025 – May 2026  

• Strong C++ skills are required 

• Experience with Python and distributed systems is very helpful 

• Familiarity with neural networks or the internals of Pytorch is nice to have 

• Performance analysis experience 

• Experience coding parallel programs