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About ZooxZoox is transforming mobility with fully autonomous, electric vehicles designed from the ground up for a dr...

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Selected role

PhD Research Intern, Vision Language Action Models

Zoox Boston, MA

$40k - $86k Senior Full-time

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

Compensation:

The monthly salary for this position is $9,500. Compensation will vary based on geographic location. Additional benefits may include medical insurance, and a housing stipend (relocation assistance will be offered based on eligibility).

About Zoox

Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

Accommodations

If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.

A Final Note:

You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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