Machine Learning Engineer Intern, Autonomy Behavior at Zoox

Foster City, California, United States

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Not SpecifiedCompensation

InternshipExperience Level

InternshipJob Type

UnknownVisa

Autonomous Vehicles, Robotics, TechnologyIndustries

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
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

Responsibilities

On the Hydra team: Explore ways to improve introspection for the ML planner and improve model performance through experiments in a hybrid planning system combining learned planner and search-based supervisor
On the Onboard Behavior Encoder team: Model and scale ML architectures for behavior decision processes; explore novel approaches to behavior modeling, including research at the intersection of LLM models and motion planning systems; drive performance improvements through rigorous experimentation
On the Prediction Integration team: Improve the performance of the ML Planner; develop innovative methods for analyzing and explaining the ML Planner's decisions

Skills

Key technologies and capabilities for this role

Machine LearningImitation LearningReinforcement LearningMotion PlanningLLMAutonomous DrivingPlanner SystemsControl SystemsML ArchitecturesSimulationExperimentation

Questions & Answers

Common questions about this position

What are the eligibility requirements for this internship?

Candidates must be currently working towards a B.S., M.S., Ph.D., or advanced degree in a relevant engineering program, returning to school after the internship, in good academic standing, able to commit to a 12-week internship in May or June 2026, have at least one previous industry internship or relevant project, and be able to relocate to the Bay Area.

Is this internship remote or does it require relocation?

The internship requires the ability to relocate to the Bay Area, California for the duration.

What is the duration and timing of the internship?

It is a 12-week internship beginning in May or June of 2026.

What kind of experience is required for this role?

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

What teams might I work on as an MLE Intern in Autonomy Behavior?

You may be assigned to the Hydra team (improving ML planner introspection and performance), Onboard Behavior Encoder team (modeling ML architectures for behavior decisions), or Prediction Integration team (improving ML Planner performance and explainability).

Zoox

Develops autonomous electric ride-hailing vehicles

About Zoox

Zoox focuses on creating a fully integrated autonomous ride-hailing service designed specifically for urban transportation. Unlike other companies that modify existing vehicles for self-driving capabilities, Zoox has engineered its own vehicle from the ground up, optimizing it for safety, efficiency, and passenger comfort. The vehicle features advanced sensors, cameras, and AI systems that allow it to navigate complex city environments. It can carry up to four passengers in a spacious interior, ensuring a pleasant ride experience. Safety is paramount, with rigorous testing and collaboration with regulatory bodies to meet high standards. Additionally, Zoox's vehicles are fully electric, promoting sustainability by reducing emissions. The company also develops a user-friendly ride-hailing platform that uses data analytics to improve routing and reduce wait times. Zoox aims to enhance urban mobility while prioritizing safety and environmental responsibility.

Menlo Park, CaliforniaHeadquarters

2014Year Founded

$1,206.2MTotal Funding

ACQUISITIONCompany Stage

Automotive & Transportation, Energy, AI & Machine LearningIndustries

1,001-5,000Employees

Benefits

Health Insurance

Maternity & Paternity Leave

Vacation & Paid Time Off

Sick Days

Free Lunch or Snacks

Employee Assitance Program

Risks

Increased competition from Waymo and Cruise may impact Zoox's market share.

Expansion into new cities introduces regulatory and operational challenges for Zoox.

Partnership with Williams Racing may divert focus from core vehicle development.

Differentiation

Zoox designs vehicles specifically for autonomous operation, unlike retrofitting existing cars.

Zoox's vehicles feature a unique, futuristic design with advanced AI systems.

Zoox offers a fully integrated ride-hailing service optimized for safety and efficiency.

Upsides

Zoox's expansion into Austin and Miami opens new markets and data collection opportunities.

Partnership with Williams Racing boosts Zoox's brand visibility in the U.S. market.

Hiring former Tesla executive Gao could accelerate Zoox's technological advancements.

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