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Wayve is building an end-to-end AI platform for autonomous driving that enables vehicles to learn directly from real-world experience. The company is pioneering a mapless, hardware-agnostic approach that adapts and generalizes at scale, partnering with global OEM manufacturers.
In this Staff-level individual contributor role, you will define and evolve the technical architecture and roadmap for Wayve's LiDAR and cross-sensor 3D sensing capabilities. You will lead the development of target-based and targetless LiDAR calibration and registration methods, including LiDAR-to-camera alignment using both geometric and learned approaches. Your responsibilities include developing robust temporal alignment and motion compensation methods using techniques such as LiDAR odometry, nonlinear least-squares optimization, and factor graphs.
You will establish evaluation methodologies and productionize reliable, scalable 3D sensing systems that operate across diverse vehicles, environments, and sensor configurations. Working with engineering and research teams, you will deliver end-to-end 3D sensing capabilities while providing technical leadership and mentorship to other engineers. This is a senior individual-contributor role with deep involvement in algorithm development, implementation, evaluation, and deployment. You will solve challenging real-world problems arising from imperfect time synchronization, rolling-shutter cameras, and LiDAR sweep patterns, developing robust methods that operate across diverse conditions.
Wayve operates a hybrid model with main hubs in London, Sunnyvale, Yokohama, Herzliya, Vancouver, and Leonberg, combining in-person collaboration with remote flexibility.
REQUIREMENTS:
Essential:
- 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 accounting for sensor timing and motion effects, such as 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 assessing calibration, registration, and 3D sensing quality across real-world conditions
- Demonstrated technical leadership, including setting technical direction, solving ambiguous cross-functional problems, and mentoring other engineers
Desirable:
- Experience with LiDAR odometry, SLAM, or mapping systems, including LiDAR motion compensation and deskewing
- Experience with metric-depth foundation models and their application to calibration, registration, or 3D reconstruction
- Familiarity with learned feature correspondences, cross-modal registration, Gaussian splatting, or other emerging 3D representations
- Experience handling dynamic scenes using object detection, motion segmentation, or tracking methods
- Practical experience with optimization libraries such as GTSAM, Ceres Solver, or g2o
