Wayve
Staff Robotics Engineer, Localisation
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The Role
Wayve is seeking a Staff Robotics Engineer, Localisation to lead the technical development of our onboard localisation capability. You will design and productionise state-estimation systems that combine GNSS, IMU and wheel odometry to provide accurate, reliable vehicle motion and pose estimates across diverse vehicles, environments and operating conditions.
This is a senior individual-contributor role with responsibility for shaping the localisation architecture and technical roadmap, while remaining deeply involved in algorithm development, implementation, validation and onboard deployment. You will work across robotics, calibration, controls, sensor, vehicle-platform and embedded-software teams to ensure localisation is robust, observable and suitable for real-time production use. You will also provide technical leadership and mentorship to engineers working across localisation and the broader state-estimation stack.
Key Responsibilities
- Define and evolve the technical architecture and roadmap for Wayve’s onboard localisation capability, aligned with vehicle programmes and product requirements.
- Lead the development of robust state-estimation systems that fuse GNSS, IMU and wheel-odometry signals, with scope to incorporate camera-, RADAR- and LiDAR-based measurements.
- Take localisation solutions from algorithm design and prototyping through production implementation and deployment on real-time vehicle platforms, including robust fault handling and degraded-mode behaviour.
- Develop rigorous validation and benchmarking capabilities, including representative datasets, ground-truth comparisons, performance metrics and regression testing across diverse vehicles, environments and operating conditions.
- Provide hands-on technical leadership and mentorship, working across robotics, calibration, controls, sensors and vehicle-platform teams to drive integration and resolve complex system-level issues.
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About You
In order to set you up for success as a Staff Robotics Engineer, Localisation at Wayve, we’re looking for the following skills and experience.
Essential
- Deep practical expertise in localisation, state estimation or sensor fusion, with experience combining GNSS, IMU and wheel-odometry measurements.
- Strong understanding of filtering-based estimation methods, including Kalman-family filters such as the EKF or UKF, and nonlinear optimisation approaches such as factor graphs.
- Experience developing and operating localisation or state-estimation systems in production robotics, autonomous vehicles or comparable real-time systems.
- Strong modern C++ software-engineering skills and proficiency in Python for prototyping, analysis, validation and test tooling.
- Experience designing rigorous localisation validation and benchmarking, including accuracy metrics, uncertainty evaluation, ground-truth comparison, regression testing and failure analysis.
- Evidence of hands-on technical leadership, including defining architecture, influencing technical roadmaps, mentoring engineers and collaborating effectively across multiple teams.
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Desirable
- Experience incorporating camera-, LiDAR- or RADAR-based measurements into localisation and sensor-fusion systems, including visual, LiDAR or RADAR odometry.
- Hands-on experience with nonlinear optimisation and robotics libraries such as GTSAM, Ceres or g2o.
- Familiarity with automotive software-development practices and coding standards, including MISRA C++.
- Experience deploying state-estimation software on embedded or resource-constrained platforms with real-time compute, memory and latency requirements.
- Experience developing high-quality ground truth, benchmarks and validation evidence for localisation or other state-estimation systems.
- Familiarity with relevant robotics tooling and libraries such as ROS, Eigen, OpenCV, PCL or CUDA.
- MS or PhD in Robotics, Computer Science, Electrical Engineering or a related field, or equivalent practical experience.
This is a full-time role based in our office in London, UK. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.
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