Zoox is looking to improve the robot's driving behaviors on public roads, specifically focusing on the complex and ambiguous pickup and dropoff scenarios, to ensure safe, reliable, and elegant user experiences for their robotaxi service.
Requirements
- Fluency in C++
- Understanding of configuration spaces and a variety of planning techniques (A*, RRTs, PRMs, etc.)
- Demonstrated ability to create real-time motion planning algorithms
- Experience working with planning problems related to pickup/dropoff or pullover maneuvers
- Experience with machine learning applications in motion planning
- Significant contributions to geometric- and/or sampling-based planning algorithms
Responsibilities
- Design principled algorithmic improvements across different driving behavior categories and implement those changes in our code base.
- Use our extensive backend tooling to test your changes across many different driving scenarios at the press of a button.
- Lead on-vehicle drive reviews to generate actionable feedback on driving performance.
- Use this experience to help the team learn and make improvements.
- Attend conferences and survey literature to stay informed on the most recent developments in the fields of Robotics and Motion Planning.
- Write and file patents for novel technologies you develop.
Other
- 8+ years of experience
- Work closely with UI/UX and product to engineer solutions that are not just safe but elegant in how they handle the different human considerations in the pickup/dropoff process.
- Passion for building the next generation of mobility-as-a-service in urban environments.
- 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.
