Contract Student Worker - Machine Learning Engineer

About Zoox

Zoox is an autonomous ridehailing company building the world's first purpose-built robotaxi — fully electric, bidirectional, with no steering wheel or driver's seat. Backed by Amazon and founded to make transportation safer, cleaner, and more accessible, Zoox designs its vehicles entirely around the rider. We're currently operating in Las Vegas and San Francisco, with Austin and Miami on the horizon, and testing underway across seven U.S. markets.

About Our Contract Student Worker Program

Zoox's contract student worker program puts you at the center of one of the most ambitious challenges in transportation. You'll contribute to real projects, work alongside engineers and researchers pushing the boundaries of autonomous technology, and gain experience that goes well beyond the classroom. We're looking for students who bring strong academic foundations, curiosity that doesn't stop at coursework, and a drive to be part of something that matters.

Role Overview

In this role, you will collaborate closely with the cross-functional engineering team to prepare and refine raw datasets, ensuring high data quality and pipeline integrity. You will assist in training and fine-tuning machine learning models using industry-standard frameworks and modern architectures. Additionally, you will validate model performance against rigorous benchmarks to ensure production readiness, reliability, and accuracy before deployment.

Responsibilities

• Review data labeling quality
• Help other engineers on model training experiments
• Validate the model results with detailed triages

Required Qualifications

• Python proficiency
• Machine learning
• Computer vision
• Robotics

Bonus Qualifications

C++

Program Requirements

• Currently enrolled in a B.S. or M.S. program in a relevant discipline.
• Available to commit to a minimum three-month assignment.
• Able to commit a minimum of 20 hours per week.
• Able to work on-site at one of our office locations.
• Must adhere with Zoox confidentiality requirements, including refraining from using or sharing proprietary company information outside of Zoox, such as in academic research, theses, publications, or presentations.