Staff Software Engineer, ML Performance Optimization

Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in ML and CV to make autonomous driving as seamless as possible. 

Are you excited to lead our ML Performance Optimization initiatives and make our Training and Inference platform that enables autonomous driving as fast and efficient as possible? You will get to work across all ML teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and Advanced Hardware Engineering group and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox.

We build and operate the base layer of ML tools, deep learning frameworks, and inference systems used by our applied research teams for in- and off-vehicle ML use cases. You will lead a team of strong software engineers and act as a force multiplier for our internal customers. This team has a lot of growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here.

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.

If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.