Contract Student Worker - Machine Learning Engineer - Data Mining & VLM (Full-time)

About The Role

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 Part-Time Student Worker Program Zoox's part-time 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 Support Zoox's Rules of the Road (RotR) program, where a miner + LLM/VLM tooling method automatically mines and triages potential road-rule violation events from simulation and fleet data. The student will be helping create or improve the data miners that generate the candidate events, help develop and evaluate the VLM triagers — curating golden datasets, measuring precision/recall against expert triage, and extending automation to new regulations and data sources.

Key responsibilities

• Develop and iterate data miners locating potential RotR Violations following SSO requirements

• Develop and iterate on VLM/LLM workflows and pipelines for classifying RotR events

• Curate golden datasets and evaluate triager precision/recall against human triage

Required Qualifications

• Extend triagers from simulation to fleet/service data

• Strong Python / Pyspark / SQL skills

• Coursework in machine learning, computer vision, or NLP. Understanding of supervised learning, model evaluation, and common sources of dataset bias and label noise.

• Analyze error cases and translate findings into pipeline improvements

• Hands-on experience building production LLM/VLM applications, including agentic workflows, RAG, tool calling, evaluation, and/or fine-tuning.

• Familiarity with software-engineering practices such as Git, unit testing, debugging, and code reviews.

Bonus Qualifications

• Strong Scala skills.

• Experience with Spark optimization and distributed data-processing systems.

• Experience with autonomous vehicles, robotics, mapping, or transportation-related datasets.

Program Requirements

• Experience evaluating multimodal or vision-language models.

• Currently enrolled in a B.S. or M.S. program in a relevant discipline.

• Experience with prompt optimization, model fine-tuning, or human-in-the-loop ML systems.

• Available to commit to a minimum three-month assignment.

• Able to commit a minimum of 40 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.

Additional information

We want to be transparent: this is not an internship. The Part-Time 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.

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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.

• Extend triagers from simulation to fleet/service data

• Strong Python / Pyspark / SQL skills

• Coursework in machine learning, computer vision, or NLP. Understanding of supervised learning, model evaluation, and common sources of dataset bias and label noise.

• Analyze error cases and translate findings into pipeline improvements

• Hands-on experience building production LLM/VLM applications, including agentic workflows, RAG, tool calling, evaluation, and/or fine-tuning.

• Familiarity with software-engineering practices such as Git, unit testing, debugging, and code reviews.

• Strong Scala skills.

• Experience with Spark optimization and distributed data-processing systems.

• Experience with autonomous vehicles, robotics, mapping, or transportation-related datasets.

• Experience evaluating multimodal or vision-language models.

• Currently enrolled in a B.S. or M.S. program in a relevant discipline.

• Experience with prompt optimization, model fine-tuning, or human-in-the-loop ML systems.

• Available to commit to a minimum three-month assignment.

• Able to commit a minimum of 40 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.

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