Staff Robotics Engineer

Job description

Job responsibilities

• Extend the capabilities of the existing online calibration node, delivering robust production software within the architecture and technical direction set by the team.
• Adapt and integrate suitable calibration and estimation algorithms for continuous or on-demand onboard execution.
• Develop reliable handling of asynchronous sensor data, accelerator-produced features and noisy, time-varying calibration parameters.
• Strengthen validation, gating, persistence and interfaces between the calibration node, onboard state, runtime consumers, logging and fleet-facing systems.
• Profile and optimise critical paths for constrained compute, memory, storage and latency budgets without compromising correctness or debuggability.
• Build comprehensive simulation, replay, bench and on-vehicle tests, and improve metrics, diagnostics and fleet-level observability across nominal and failure scenarios.

Job requirements

• Strong practical expertise in sensor calibration, state estimation or a closely related robotics domain, including calibration of cameras, LiDAR, IMUs, vehicle parameters or multi-sensor systems.
• Strong understanding of filtering and estimation methods, such as Kalman-family filters, Bayesian estimation, smoothing, robust estimation or factor-graph optimisation.
• Strong modern C++ software-engineering skills and proficiency in Python for prototyping, analysis and test tooling.
• Experience productionising algorithm-heavy robotics software for vehicles, robots, drones, aerospace systems or comparable edge platforms, including clear lifecycle, failure-handling and recovery behaviour.
• Experience with asynchronous, high-throughput sensor data and hardware-accelerated pipelines, with the ability to optimise constrained compute and memory systems without losing correctness or debuggability.
• Strong software architecture, API design, testing, debugging and performance-profiling skills, with evidence of end-to-end ownership and effective cross-functional collaboration.
• Experience in visual odometry, SLAM, localisation, sensor fusion, ego-motion estimation or geometric computer vision.
• Experience with GPU, DSP, NPU or other hardware-accelerated robotics workloads, including zero-copy or shared-memory data paths and optimisation for production runtime constraints.