Contract Student Worker - Machine Learning Engineer - Data Mining & VLM (Full-time)
Zoox is hiring a Contract Student Worker - Machine Learning Engineer - Data Mining & VLM (Full-time) in Foster City, United States. Level rates it ; you can apply on Zoox.
Level's read on this job
- Builds AI ●●●● is how Level rates this machine learning engineer role: the job is building AI systems.
- The posting mentions RAG, AI agents and fine tuning among its tools and skills.
- Zoox has 224 other open roles on Level.
AI in this 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.
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.
About ZooxZoox 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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AccommodationsIf 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.
How we rate this
Contract Student Worker - Machine Learning Engineer - Data Mining & VLM (Full-time) at Zoox rates 93 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in machine learning engineer jobs at this level
Pay
- Typical machine learning engineer job
- $200k
This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you decide that one model's output is better than another's for a given task?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, Fine-tuning, AI Evaluation, and Computer vision. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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