Robotics Jobs in Woking

Wayve · London

Hands-on role optimising inference for edge accelerators and GPUs so large transformer models run efficiently on low-cost, low-power in-vehicle compute. You'll profile model graphs, compilers, runtimes and kernels, implement optimisations like fusion, scheduling and custom kernels, and build benchmarking and regression tests across NVIDIA Orin/Thor and Qualcomm targets, working closely with model, platform and deployment teams.

Wayve · London

Builds and evolves the data pipeline and orchestration platform behind Wayve's autonomous driving data, revamping the existing Harness system and creating a new DAG-based workflow platform. Works on Kubernetes-deployed, distributed infrastructure handling hundreds of parallel pipeline steps, batch inference and evaluation workflows, closely with partner teams.

Humanoid · London

Own the hardware test methodology for a humanoid robot platform, defining component, subsystem and whole-robot tests from bench actuators to full walking integration sequences. Hands-on role: bring up prototypes, root-cause failures, and specify fixtures, jigs and production test requirements with Manufacturing Engineering and Quality. Sets pass/fail criteria, tolerances and traceable test data as the programme moves from EVT to production.

Humanoid · London

Own the hardware test methodology for a humanoid robot platform, defining component, subsystem and whole-robot tests and running them hands-on on early prototypes. Partner with automation, manufacturing and quality teams to translate methods into production test rigs, in-process checks and traceable acceptance criteria from EVT toward production.

Wayve · London

Builds and ships computer vision and 3D perception models for driver assistance, working across the full ML lifecycle from data generation to training, evaluation and iteration. The role spans latency-constrained on-car perception and large-scale offline work using lidar, maps and extra compute to power an auto-labelling data flywheel.

Wayve · London

Bridges Wayve's core AI Driver architecture and OEM/Tier 1 vehicle platforms, defining software–vehicle interfaces across sensors, signals, middleware and ECUs. Owns interface contracts, ownership boundaries and validation-ready requirements, representing Wayve in partner technical discussions.

Wayve · London

Builds and maintains core C++/Python components that interface self-driving models with vehicle and embedded systems, plus infrastructure to run and test autonomy capabilities. Owns reliability and performance of Linux-based systems and specialises in one domain such as localisation/mapping, filtering/diagnostics or control/inference, in a team scaling to 5-6 engineers.

Wayve · London

Develops next-generation generative world models and planners such as GAIA, using diffusion, transformer and hybrid architectures to simulate complex driving environments for training, testing and deployment. The role spans ML research, multi-modal modelling and real-world deployment, with a focus on inference efficiency, closed-loop agent interaction and sim-to-real evaluation.

Wayve · London

Owns validation strategy for ADAS and L2 autonomy functions, translating product, safety and regulatory requirements into test scenarios, metrics, coverage and acceptance criteria. Works hands-on with Python evaluation pipelines, simulation and SQL data analysis, and can be hired as a senior individual contributor or as a manager leading validation delivery.

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

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 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

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.