Internship, Software Engineer, Machine Learning Infrastructure (Winter/Spring 2025)

What to Expect

Consider before submitting an application:

This position is expected to start around January or February 2025 and continue through the entire Spring term (i.e. through May 2025) or into Spring/Summer 2025 if available. We ask for a minimum of 12 weeks, full-time and on-site, for most 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.

Internship Program at Tesla

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.

About the Team

As a Software Engineer for the Tesla Autonomy team, you will build infrastructure to facilitate neural network architecture design and large-model scaling, improve distributed training speed, curate complex dataset generation, and build tools for visualizing data and evaluating experimental results. You will help us automate the entire workflows of training, validation, and production for (Supervised) Full Self Driving. Most importantly, you will see your work repeatedly shipped to and utilized by a vast fleet of cars actually driving on the road.

The topics above outline the breadth covered by our team. Typically interns work with their leads to craft a project in one (or some) of these areas based on their interests and the current needs of the team at the time they join.

What You’ll Do

Build and improve our AI infrastructure for stable, vastly distributed, and faster training
Build the tooling and infrastructure for reporting and visualizing model metrics and performance
Build the pipelines to run and validate our PyTorch models
Manage, analyze, and visualize our training and test datasets
Coordinate with the team managing the hardware cluster to maintain high availability / jobs throughput for Machine Learning
Build and improve tooling to deploy trained neural nets to Tesla hardware

What You’ll Bring

Pursuing a degree in Computer Science, Computer Engineering, or relevant field of study with a graduation date between 2025 -2026
Must be able to relocate and work on site in Palo Alto, CA
Practical experience programming in Python and C++
Proficient in system-level software, particularly hardware-software interactions and resource utilization
Understanding of modern machine learning concepts and state of the art deep learning
Experience working with training frameworks, ideally PyTorch
Demonstrated experience scaling neural network training jobs across a cluster of GPU’s
Experience in deep learning deployment or profiling/optimizing CPU-GPU interactions preferred