1 day ago
London, United KingdomStaff+
Responsibilities
- Define and evolve the technical architecture and roadmap for LiDAR and cross-sensor 3D sensing capabilities.
- Develop target-based and targetless LiDAR calibration and registration methods, including LiDAR-to-camera alignment using geometric and learned approaches.
- Develop temporal alignment and motion compensation methods using LiDAR odometry, nonlinear least-squares optimization, and factor graphs.
- Establish evaluation methodologies and productionize reliable, scalable 3D sensing systems across vehicles, environments, and sensor configurations.
- Deliver end-to-end 3D sensing capabilities with engineering and research teams while providing technical leadership and mentorship.
Requirements
- Significant experience developing robotics or autonomous-driving systems involving LiDAR, cameras, and 3D sensor data.
- Strong experience with target-based or targetless sensor calibration and registration, including LiDAR-to-camera alignment.
- Strong understanding of 3D geometry, state estimation, and optimization techniques, including nonlinear least-squares methods or factor graphs.
- Experience handling sensor timing and motion effects, including time synchronization, LiDAR sweep distortion, rolling-shutter cameras, and motion compensation.
- Strong software-engineering skills in C++ and/or Python, with experience taking robotics algorithms from prototype through evaluation and production deployment.
- Experience defining evaluation methodologies, datasets, and metrics for calibration, registration, and 3D sensing quality in real-world conditions.
- Demonstrated technical leadership through setting technical direction, solving ambiguous cross-functional problems, and mentoring engineers.
- Experience with LiDAR odometry, SLAM, or mapping systems is desirable.
- Experience with metric-depth foundation models, learned feature correspondences, cross-modal registration, Gaussian splatting, or other emerging 3D representations is desirable.
- Experience handling dynamic scenes with object detection, motion segmentation, or tracking methods is desirable.
- Practical experience with GTSAM, Ceres Solver, or g2o is desirable.
Benefits
- Full-time role based in Wayve’s London, UK or Sunnyvale, US office.
- Hybrid working policy combining time in offices and workshops with time working from home.
- Inclusive interview experience with accommodations or adjustments available upon request.
