Our Calibration, Localization, and Mapping (CLAMS) team is responsible for building the algorithms and tools necessary for keeping Zoox vehicles well calibrated, always knowing where they’re located within the world, and aware of their environment. Without precise calibration, localization, and mapping our vehicles would be at a disadvantage when it comes to perceiving and reasoning about the surrounding world, and is therefore foundational in enabling results from many other teams across Zoox. This work is critical for scaling autonomous driving in a safe and reliable way. We are looking for engineers who are ambitious and excited about helping Zoox deliver on its goals to deliver autonomous mobility.
Investigate and develop rigorous, cutting-edge solutions to challenging structured and unstructured calibration problems
Solve algorithmic problems that will allow Zoox to build a highly automated, verifiable, and scalable calibration system
Develop techniques to enable on-vehicle monitoring of sensor calibration quality
Determine the best way to calibrate new sensor modalities
Masters or PhD in a robotics-related field
Proficiency in C++
Proficiency in probability and statistics
Experience with non-linear least squares optimizations
Has a humble passion for getting the details right
Experience with spatial data structures
Experience with multiple sensor modalities
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.
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.