Principle Engineer, 3D Reconstruction
Core
Lead the development of an offline 3D reconstruction system that builds high-quality 3D world geometry from vehicle sensor data in dynamic scenes to support internal validation, data enrichment, and model development.
Role type
Principal Engineer, 3D Reconstruction
Builds
Offline 3D geometric reconstructions and best-estimate ego motion from heterogeneous vehicle platforms and sensor suites
Domain
Autonomous driving, robotics, sensor fusion
Deliverable
production ML models
Required skills
SLAM, 3D reconstruction, mapping, state estimation, lidar-based reconstruction, point-cloud registration, pose estimation, C++, Python, nonlinear optimization (pose graph optimization, factor graphs, bundle adjustment, ICP), sensor calibration, timing synchronization
Preferred skills
MS/PhD in Robotics/CS/State Estimation, autonomous vehicles experience, GNSS/INS fusion, modern machine learning for 3D reconstruction, ROS, PCL, OpenCV, CUDA, ML data enrichment workflows, leading expert technical teams
Technologies
C++, Python, ROS, PCL, OpenCV, CUDA
Responsibilities
Define technical architecture and roadmap for offline 3D reconstruction system; Lead development of MVPs to unblock high-priority internal use cases; Establish core technical interfaces, output representations, and tools; Partner with calibration, sensor fusion, perception, data, infrastructure, and validation teams; Set technical standards for reconstruction quality, failure analysis, uncertainty measurement, and dataset suitability; Mentor and provide technical leadership to engineers contributing to the 3D reconstruction effort
Seniority
Principal, technical leadership & strategy
