Staff Robotics Localization Engineer - Hybrid (London)

Wayve; London (KY); Hybrid; USD 119,000 - 172,000; Full time

Job summary

Wayve is seeking a Staff Robotics Engineer, Localisation to lead the onboard localisation capability. You will design state-estimation systems that fuse GNSS, IMU and wheel odometry for accurate vehicle pose estimates and real-time operation.

This senior individual-contributor role includes shaping the localisation architecture, roadmap, and hands-on algorithm development with deployment across vehicle platforms.

Qualifications

• Deep expertise in localisation, state estimation, or sensor fusion including GNSS/IMU/wheel-odometry.
• Strong knowledge of filtering methods (EKF/UKF) and factor graphs.
• Experience deploying state-estimation in production robotics or real-time systems.
• Proficient C++ with Python for prototyping and tooling.
• Ability to design validation, benchmarking, and failure analysis.
• Proven technical leadership across multiple teams.

Responsibilities

• Define architecture and roadmap for onboard localisation aligned with vehicle programs.
• Develop robust state-estimation systems fusing GNSS, IMU, wheel-odometry; extend with camera/RADAR/LiDAR data.
• Move solutions from prototype to production on real-time vehicle platforms with fault handling.
• Create validation datasets, metrics, regression tests and performance benchmarks.
• Lead and mentor engineers across robotics, calibration, controls and software teams.

Skills

Localization

State Estimation

Sensor Fusion

Kalman Filters

C++

Python

Production Robotics

Technical Leadership

Education

MS/PhD in Robotics or related

Tools

GTSAM

Ceres

ROS

Eigen

OpenCV

PCL

CUDA

Job description

Wayve is seeking a Staff Robotics Engineer, Localisation to lead the onboard localisation capability. You will design state-estimation systems that fuse GNSS, IMU and wheel odometry for accurate vehicle pose estimates and real-time operation.

This senior individual-contributor role includes shaping the localisation architecture, roadmap, and hands-on algorithm development with deployment across vehicle platforms.