Zoox is a purpose-built autonomous vehicle designed for riders, not drivers. Learn more about the Zoox robotaxi and the future of ride-hailing. Backed by Lux.
About the role
As a Staff or Senior Staff engineer, you will be the technical lead for CAS algorithms, with a focus on CAS perception. You will shape how CAS sees the world, combining interpretable geometric methods with machine learning, and you will own the architecture and roadmap that take these capabilities from idea to safe, real-time deployment on our fleet. Your work will directly affect the safety of every rider and road user around our vehicles. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Serve as the technical lead and architect for CAS perception, defining how lidar, radar, and camera data become reliable obstacle detection, tracking, and collision-risk estimates under tight latency and compute budgets
- Own the end-to-end CAS algorithm architecture and multi-release technical roadmap, making clear trade-offs between safety, performance, latency, compute, and ML vs. non-ML approaches
- Partner across CAS perception, behavior and planning, and validation to define interfaces, requirements, metrics, and evaluation strategies that show the system is safe and ready to launch
- Work with sensor, system performance, safety strategy, and main autonomy teams to drive cross-team technical decisions, while mentoring engineers and raising the technical bar across CAS
More about this role
The Collision Avoidance System (CAS) is Zoox's independent safety layer. It runs alongside our main autonomy stack, constantly watches for imminent collisions, and reacts within milliseconds to prevent or reduce them. By using different methods and data paths than the main stack, CAS gives our robotaxi a second, diverse line of defense in the most challenging dense urban environments.
As a Staff or Senior Staff engineer, you will be the technical lead for CAS algorithms, with a focus on CAS perception. You will shape how CAS sees the world, combining interpretable geometric methods with machine learning, and you will own the architecture and roadmap that take these capabilities from idea to safe, real-time deployment on our fleet. Your work will directly affect the safety of every rider and road user around our vehicles.
- Serve as the technical lead and architect for CAS perception, defining how lidar, radar, and camera data become reliable obstacle detection, tracking, and collision-risk estimates under tight latency and compute budgets
- Design, implement, and ship both machine learning and classical perception algorithms (e.g., point-cloud geometry, ground estimation,...
Browse similar: Startup jobs