1 month ago
Responsibilities
- Architect behavior-planning logic and decision frameworks for complex autonomous-driving maneuvers.
- Develop trajectory-generation systems balancing safety, passenger comfort, and vehicle progress.
- Translate traffic rules and operational design domain constraints into interpretable, safe planning behaviors.
- Address long-tail autonomous-driving scenarios involving pedestrians, occlusions, and construction zones.
- Integrate planning with perception, prediction, localization, and control modules.
- Validate solutions through scenario-based simulation, closed-course trials, and live on-road testing.
- Optimize deterministic, real-time performance for embedded automotive hardware.
- Collaborate with sensor and compute vendors, AI teams, and customers.
Requirements
- MS or PhD in robotics, computer science, or electrical engineering, or equivalent industry experience.
- Strong C++ skills for robust real-time systems and Python skills for tooling and data analysis.
- Deep familiarity with search-, sampling-, and optimization-based planning algorithms.
- Experience with decision architectures such as finite-state machines and behavior trees.
- Understanding of vehicle kinematics and dynamics.
- Hands-on experience with ROS, ROS2, or comparable autonomous middleware.
- Experience shipping a planner on public roads and analyzing real-world disengagement data is preferred.
- Experience with CARLA or custom scenario frameworks is preferred.
Benefits
- Competitive health insurance options.
- 401(k) plan management.
- Remote-friendly and flexible team culture.
- Free lunch and a fully stocked kitchen at the South Bay office.
- Monthly wellness stipend, office setup allowance, company retreats, and additional perks.
- Opportunity to work on autonomous-driving technology.
