Motion Planning Intern

zoox

4100

Foster City, CA, United States

Posted on: 2025-11-12

Category: emobility

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Employment type:

Internship

Experience required:

Intern

Salary

Salary not provided

About the company:

Zoox is transforming mobility-as-a-service by developing a fully autonomous, purpose-built fleet designed for AI to drive and humans to enjoy.

Zoox’s internship program provides hands-on experiences with state of the art technology, mentorship from some of the industry's brightest minds, and the opportunity to play a part in our success. Internships at Zoox are reserved for those who demonstrate outstanding academic performance, activities outside their course work, aptitude, curiosity, and a passion for Zoox's mission.

As a Motion Planning Intern, you may be matched with one of the following teams:

On the Collision Avoidance Systems team, you will build and optimize core autonomy software including planning algorithms, collision avoidance systems, trajectory generation and validation, or real-time decision-making systems. Implement efficient data structures for tree search, develop cost evaluation functions, or work on CAS components like trajectory validators, collision checkers, and safety perception systems. Write high-performance C++ code that runs on our vehicles.

On the Fail Operational Planner team, you will explore ways for Planner to continue operating effectively, even in the presence of degraded capabilities or limited failures. The focus of the team includes developing behavioral and motion planning capabilities in degraded state to improve trip progress metrics, and correspondingly a better customer experience. In this role, you will develop algorithms to implement new behaviors or improve upon the performance of existing ones for specific failure modes while collaborating with a diverse group of experts including Planner, Perception, Prediction, and Hardware.

On the Framework & Search team, you will explore ways to improve our planner’s strategic decision making capabilities. We model long horizon concerns so that our planner can make informed decisions such as when best to lane change when following a route. In this role you will develop algorithms to improve the fidelity of our long horizon motion planning models. This will involve collaborating with other teams, simulation-based and real world validation, and creating new introspection tools.

Compensation:

The monthly salary range for this position is $5,500 to $9,500. Compensation will vary based on geographic location and level of education. 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.

Requirements:

Currently working towards a B.S., M.S., Ph.D., or advanced degree in a relevant engineering program

Must be returning to school to continue your education upon completing this internship

Good academic standing

Able to commit to a 12-week internship beginning in May or June of 2026

At least one previous industry internship, co-op, or project completed in a relevant area

Ability to relocate to the Bay Area, California 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