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Contract Student Worker - Machine Learning Engineer

ZooxBoston🇺🇸United States

Quick overview

Salary$30/hr
SeniorityMid Senior
Employment typeTemporary/Casual
Work modeOn Site
LocationBoston, United States
RoboticsComputer VisionC++PythonMachine Learning

Job description

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.
We want to be transparent: this is not an internship. The Contract Student Worker Program is designed to complement your academic experience by providing meaningful, ongoing work alongside your studies. Rather than participating in a cohort-based program, you'll join a team directly and contribute to real projects with real impact. While the program does not include structured intern programming or a pathway to full-time employment, it offers valuable opportunities to learn, develop new skills, and gain hands-on experience in a professional environment.
Compensation for this role is $30/hour.
This is a contract position; employment will be through a vendor contracted with Zoox. The hourly rate is as posted, and benefits eligibility is determined by the vendor.
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 accommodations@zoox.com 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.

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