About Zoox
Zoox is transforming mobility with fully autonomous, electric vehicles designed from the ground up for a driverless future. Our mission is to make transportation safer, more sustainable, and accessible to everyone. At Zoox, innovation, collaboration, and a bold vision for the future drive everything we do.
About Our Internship Program
Zoox’s internship program offers hands-on experience with cutting-edge technology, mentorship from some of the industry’s brightest minds, and the opportunity to make meaningful contributions to real projects. We seek interns who demonstrate strong academic performance, engagement beyond the classroom, intellectual curiosity, and a genuine interest in Zoox’s mission.
Project Overview
This internship opportunity is within the Foundation Models team which focuses on advancing the state of the art in autonomous driving: Multimodal Language Action models (MLA), massively scaling reinforcement learning for agent policies, and more.
You will have the chance to work on our Multimodal Language Action model, exploring novel discrete action tokenization and flow matching approaches, building off of MotionLM, FAST and others. You’ll train models at the billion+ scale on millions of miles of proprietary Zoox driving data. You’ll gain valuable experience and insight into training MLAs at scale. This project will contribute to publishable research, and could make it into our vehicle.
Requirements
- Currently working towards a Ph.D., or advanced degree in a relevant engineering program
- Good academic standing
- Able to commit to a 12-week internship during one of the following summer 2026 cohorts: May 18th - August 7th OR May 26th - August 14th OR June 15th - September 4th
- Ability to relocate to the Bay Area, California (or Boston, Massachusetts) for the duration of the internship
- Interns at Zoox may not use any proprietary information they are working on as part of their thesis, any published work with their university, or to be distributed to anyone outside of Zoox
Qualifications
- Experience training VLMs, or VLAs
- Experience working in large codebases as part of a team
- Advanced understanding of Python and PyTorch
- Has authored publications in top ML/robotics conferences (e.g. NeurIPS, CVPR, ICRA, etc)
Bonus Qualifications
- Experience with autonomous driving
- Experience with machine-learning-based robotic planning
- Experience with large-scale, multi-node Pytorch workloads
