Robotics Jobs in Woking

Humanoid · London

Designs, implements and validates actuator- and joint-level controllers plus grasp-level behaviours for a family of end-effectors, including parallel and multi-finger grippers, vacuum tooling and underactuated designs. Works in ROS2 and C++ from real-time embedded control through kinematics, dynamics, transmission modelling and hands-on hardware bring-up, shaping actuation and transmission choices with mechanical engineers early in the design cycle.

Humanoid · London

Lead operational execution across the company, owning the company-wide execution framework including roadmaps, delivery plans, timelines and milestones. Drive cross-functional alignment between engineering, product and leadership, monitor progress, resolve delivery risks and bottlenecks, and provide oversight to project managers. Distinct for its deep-tech robotics context and executive-level ownership of strategy-to-execution.

Wayve · London

Hands-on role bringing up new vehicle platforms on benches, HiL systems and vehicles, developing vehicle-facing software and shared frameworks in C++, Python or Rust. Involves diagnosing software/hardware integration issues across Linux, ROS2, sensors, CAN and Automotive Ethernet, plus building diagnostics and tooling for robot-software reliability.

Wayve · London

Builds ground-truth datasets and computer vision classifiers that describe complex driving scenes across Wayve's data corpus, tackling road geometry, spatial relationships, road users and driving behaviour. Works with internal customers to define attributes and acceptance criteria, designs annotation tasks, and integrates classifiers with enrichment infrastructure for corpus analysis and scenario mining.

Wayve · London

Owns the technical architecture and roadmap for LiDAR and cross-sensor 3D sensing, leading development of target-based and targetless calibration, LiDAR-to-camera registration, temporal alignment and motion compensation using LiDAR odometry, nonlinear least-squares optimisation and factor graphs. A senior individual-contributor role combining algorithm development, evaluation methodology and productionisation, with technical leadership and mentorship across the 3D sensing stack.

Wayve · London

Lead functional safety activities for an end-to-end AI automated driving system, building Item Definitions, running HARA/FMEA/FTA analyses, and shaping safety concepts and architectures across vehicle platforms and third-party systems. Define verification and validation, including vehicle-level testing, and construct structured safety cases with claims, arguments and evidence for certification.

Wayve · London

Lead a newly dedicated Runtime Platform team building the application frameworks, middleware, IPC, performance and observability foundations that let Wayve's AI Driver run in real time onboard vehicles. The role is people-first, combining coaching, hiring and roadmap ownership with technical direction across latency, profiling, real-time scheduling and embedded Linux, partnering with vehicle software, hardware and OEM programme teams.

Wayve · London

Owns the technical vision and architecture for a platform that lets model engineers deploy, run, evaluate and improve ML models over petabytes of driving data on large GPU fleets. Combines hands-on backend engineering in Python with cross-team technical leadership, mentoring senior engineers and leading a small team of 2-3.

Wayve · London

Owns the end-to-end architecture and technical roadmap for Remote Assistance, the real-time bridge between Wayve's AI Driver and human operators, spanning onboard vehicle integration, offboard services and operator HMI. Defines the vehicle-operator contract, fallback/MRM behaviour and latency budgets, and leads cross-org execution across autonomy, safety, platform and product teams to support the L4 safety case.

Wayve · London

Owns the engineering release process for autonomous driving models, defining branching strategies, release cadence, configuration management and quality gates. Reviews model, architecture and code changes against intended outcomes, assesses evaluation results for safety and performance, and builds CI/CD tooling and observability to catch issues earlier. Works across ML engineering, AI Platform, evaluation and product teams, balancing delivery speed with release rigour.

Wayve · London

Owns shared onboard runtime foundations for autonomous vehicles: application frameworks, communication middleware, lifecycle management, health monitoring and observability. Day to day involves C++ development, end-to-end latency and performance profiling across OS scheduling, memory hierarchy and thread synchronisation, plus porting the stack to new operating systems and compute platforms.

Wayve · London

You'll design, build and operate shared infrastructure for model access, agent runtimes and observability, taking projects from problem definition through technical design, deployment and ongoing operation. Working closely with security, IT and engineering, you'll create governed access layers, reusable tooling and standards so teams can run AI agents in production without one-off infrastructure.

Wayve · London

Develops and maintains production-quality components in Wayve's shared simulation system, working hands-on in a modern C++ and Python codebase. Integrates driving-stack components, simulated robot systems and vehicle-platform capabilities, initially focused on high-scale open-loop evaluation. Investigates on-road versus simulated behaviour differences and improves reproducibility, observability and simulator performance.

Wayve · London

Sets technical strategy and roadmap for fault detection and fallback systems in an autonomous driving stack, designing and training detection mechanisms for robust driverless operation. Leads integration into the shared driving stack, aligning ML, inference optimisation and software teams, and mentors through architecture reviews. Works with large-scale training and fleet data in a small, high-impact team.

Wayve · London

Lead a team of ML engineers and applied scientists building a production synthetic-data engine from generative world models like GAIA-3, covering rig and pose transfer, controllability and large-scale GPU inference. Own the loop from checkpoint and config through generation, evaluation and training, while driving inference optimisation, valid-generation yield and cross-team integration with driving-model and safety teams.