Machine Learning Engineer Intern, Autonomy Behavior

Posted 4 Days Ago
Foster City, CA
Hybrid
6K-10K Annually
Internship
Artificial Intelligence • Machine Learning • Robotics • Software • Transportation • Design • Manufacturing
Zoox is an autonomous mobility company that’s created a purpose-built robotaxi to give the world a better way to ride.
The Role
The Machine Learning Engineer Intern will assist with planning and control systems for autonomous vehicles, focusing on ML model performance and behavior decision processes, while collaborating with experts in the field.
Summary Generated by Built In
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.

The Autonomy Behavior group at Zoox develops the planning and control systems that enable the vehicle to make safe, comfortable, and efficient driving decisions. These engineers work on planner capabilities, control systems, behavior compute and integration, onboard behavior model architectures, and data optimization to ensure our robotaxi drives safely and naturally in complex urban environments.

As an MLE Intern working on Autonomy Behavior, you may be assigned to one of the following teams:

On the Hydra team, you will explore ways to improve introspection for the ML planner as well as improve model performance. This team is developing a hybrid planning system that combines a learned planner component with a search based supervisor system. In this role, you will be exploring improving the introspectability of the learned planner as well improving the performance through experiments. You will have the opportunity to learn from world class experts on Imitation Learning, Reinforcement Learning and potential to demonstrate your work both in simulation and on our robots.

On the Onboard Behavior Encoder team, you will be responsible for modeling and scaling ML architectures that enable behavior decision processes in autonomous vehicles. In this role, you'll explore novel approaches to behavior modeling, including research at the intersection of LLM models and motion planning systems. You'll drive performance improvements through rigorous experimentation and have the opportunity to work alongside world-class ML researchers and autonomous driving experts. Your contributions will directly influence how our vehicles navigate complex real-world scenarios.

On the Prediction Integration team, you will be a key contributor to the autonomous vehicle's real-world driving behavior by improving the performance of the ML Planner. This role offers the chance to develop innovative methods for analyzing and explaining the ML Planner's decisions. You will also benefit from learning directly from leading experts in autonomous driving and ML research.

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

Qualifications:

  • Advanced understanding of Python or C++
  • Strong experience with PyTorch and/or JAX
  • Experience with production ML pipelines: dataset creation, labeling, training, metrics
  • Experience with Neural Network design and implementation
  • Strong track record in machine learning for autonomous driving, robotics, or LLMs

Bonus Qualifications:

  • Publication at top-tier conferences (e.g., NeurIPS, ICML, CoRL, CVPR, ICCV, ECCV, IROS, ...)
  • Familiarity with applying ML visualization and introspection techniques

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.

Follow us on LinkedIn

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.

Top Skills

C++
Jax
Python
PyTorch
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The Company
HQ: Foster City, CA
2,500 Employees
Year Founded: 2014

What We Do

Zoox is an autonomous mobility company that was founded to provide a safer, cleaner, and more enjoyable future on the road. To achieve that goal, the company has spent the past 10 years creating a purpose-built robotaxi that gives the world a better way to ride.

Why Work With Us

At Zoox, we are working to solve one of the greatest technological challenges of our generation.
From the beginning, we have been focused on our goal of reimagining transportation from the ground up. We are a mission-driven community of innovators working together to create a safer, cleaner, and more enjoyable future on the road.

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