This internship opportunity is with the Offline Driving Intelligence team working on ML-Agents, within Zoox’s broader Foundation Models organization. The team focuses on creating agents that behave like humans (in driving simulation environments). We are developing multi-agent simulation, tackling open research problems at the frontier of large-scale reinforcement and imitation learning.
Interns on this team will have the opportunity to develop state-of-the-art agent policies, contribute to publishable research, and receive mentorship from experienced researchers in the field. Interns will work with a mentor to address a major open research question currently facing the team. There is a direct path from the novel research of this internship to being used in production as part of the simulation system that tests Zoox’s autonomous driving software.
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, CA or Seattle, WA 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 with imitation learning (both behavior cloning and closed-loop methods)
- Experience with online reinforcement learning
- Advanced understanding of Python, PyTorch, and Jax
- Experience working in large codebases as part of a team
- Has authored publications in top ML/robotics conferences (e.g. NeurIPS, CVPR, ICRA, etc)
Bonus Qualifications
- Experience with autonomous driving
- Experience with robotics planning
- Experience with inverse reinforcement learning
- Experience with multi-agent reinforcement learning
