Zoox is transforming mobility-as-a-service by developing a fully autonomous, purpose-built fleet designed for AI to drive and humans to enjoy.
Zoox is looking for machine learning engineers to help build systems to evaluate and improve autonomous driving behaviors by learning from expert human drivers. Our team develops core technologies to benchmark our vehicles against expert human driving and tune driving software toward more human-like behaviors. These systems are critical for ensuring safe, comfortable, and natural driving experiences for our riders.
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
[email protected] 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.
In this role, you will:
Design and build ML systems that learn from expert human driving data to model human-like driving behaviors.Develop evaluation methods that measure the human-likeness of autonomous driving.Develop AutoML systems to optimize autonomous driving software and improve alignment with expert human drivingWork with large-scale datasets and distributed training pipelines to deliver production-ready ML solutions.Collaborate cross-functionally with planner, simulation, and infrastructure teams to drive measurable improvements in vehicle behavior.Qualifications:
BS/MS/PhD in Machine Learning, Computer Science or equivalent experienceProficiency in Python and PyTorch, with experience building ML systemsBackground in training, evaluating, and deploying ML modelsComfortable working with large datasets and distributed compute platforms