Manager, Data Science for Collision Avoidance

The Collision Avoidance System (CAS) is responsible for detecting and reacting to imminent collision situations in support of our vehicle’s overall safety goals. CAS Perception is responsible for processing raw sensor data from our vehicle’s world-class sensor suite using a combination of geometric, interpretable algorithms and deep learning to detect near-collisions with obstacles along our intended driving path, in the most challenging dense urban environments and under tight compute resource constraints. Overall CAS is parallel and complementary to our Main AI autonomy stack and has a close relationship with our vehicle hardware and safety teams to architect redundancy into our overall driving system.

As the Manager, Data Science for CAS (CAS Verification and Validation) at Zoox, you will spearhead a multifaceted team comprising engineers, data scientists, and statisticians, focusing on the critical task of assessing the Collision Avoidance System (CAS). This system is essential for detecting and mitigating imminent collisions, through partnering with Zoox's autonomy software teams. Your role involves defining and building metrics to gauge CAS performance, emphasizing its operation in dense urban settings. You will collaborate extensively with System Engineers and QA teams to formulate comprehensive validation plans, ensuring CAS's efficacy and integration within Zoox's broader safety objectives.