About the role
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.
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.