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Develop motion planning, decision-making, vehicle control, and estimation algorithms for autonomous vehicles. Implement mission-critical real-time C++ for embedded automotive systems, build simulation and analysis tools in Python and C++, integrate with perception and platform teams, validate software on vehicles, define safety and performance metrics, analyze field data, and implement safety mitigations.

Design and implement multi-sensor state estimation for radar-centric autonomy. Develop tightly coupled fusion of camera, radar, and IMU for localization, mapping, calibration, odometry, and real-time navigation. Deliver production-ready, low-latency algorithms, optimize for embedded constraints, and drive architectural and reliability improvements validated on real vehicles.

Design and implement trajectory planning and decision-making algorithms and vehicle control for autonomous vehicles. Write production-quality, real-time C++ and Python tooling, build simulation and validation systems, integrate planning with perception and platform teams, and drive on-vehicle testing, tuning, and safety analyses to deploy robust driving behaviors.

As a Sensor Fusion & Localization Engineer, you will develop algorithms for localization, mapping, and sensor fusion to enable autonomous systems. You will architect a multi-sensor state estimation system and ensure reliability and real-time performance in robotic applications.

Join the Platform team to integrate sensors and perception models, develop and maintain data-collection and demo infrastructure, drive software standards, and deliver production-ready features across embedded, backend, and UI layers.