Robotics Jobs in Woking

Humanoid · London

Teleoperate humanoid robots and follow structured procedures to generate high-quality datasets for training AI models, using on-site tools such as the Universal Manipulator Interface. A large part of the work is annotating and labelling multimodal data with precision, escalating anomalies and suggesting workflow improvements. Full training is provided and no technical background is required.

Humanoid · London

Lead the design of state estimation, long-term mapping and localisation loops, integrating modern machine learning and foundation geometry models into the core navigation stack. Train and deploy large-scale multimodal networks for ultra-low latency performance on edge hardware, building 3D spatial representations that give robots persistent spatial memory. Works cross-functionally between research and reliable robot integration.

Wayve · London

Post-train and scale GAIA-family large video diffusion world models to generate multimodal synthetic driving data, running generation pipelines across tens of thousands of segments and optimising GPU inference. Sits between ML research and engineering, landing synthetic data into the same training stack as real driving data and measuring its impact on driving-model performance.

Wayve · London

Owns the end-to-end release cycle for AI driving models, coordinating ML engineering, evaluation, data science, platform, testing and product teams. Defines release gates and promotion criteria from training through validation to fleet deployment, drives regression investigations and rollback decisions, and builds tooling and KPIs to remove bottlenecks in a non-deterministic ML environment.

Wayve · London

Own a substantial work package end-to-end, defining the problem, setting strategy and sequencing work to advance an end-to-end AI driving platform. Lead a cross-functional team of engineers, researchers and PMs without formal authority, translating R&D progress and customer needs into a clear product roadmap with tracked KPIs and milestones.

Wayve · London

Lead a distributed team of seven engineers owning network and site infrastructure across offices, garages, labs and test facilities in six countries. The role combines people leadership with roughly 20% hands-on work, driving a multi-year network replacement, site builds, automation and security controls, plus on-call and regular international travel.

Wayve · London

Builds reusable Python libraries and platform tooling for multimodal data loading, distributed training, checkpointing and observability, supporting ML teams running models across thousands of GPUs. Partners closely with researchers to turn complex workflows into stable, scalable software, leading projects from discovery to delivery. A platform engineering role rather than ML modelling.

Wayve · London

Lead the Applied Methods Data Science team, partnering with the Autonomy organisation to turn experimental and observational analysis of real and simulated driving into evaluations and insights. Set three-, six- and 12-month roadmaps, review technical proposals for statistical rigour, and grow the team through hiring, tooling and automation.

Wayve · London

Build and operate backend services, APIs and data-processing workflows for a platform that deploys, runs and evaluates ML models over petabytes of driving data on large GPU fleets. Work spans model-execution workflows, versioned outputs, annotation and dataset-catalogue features, plus reliability, scheduling and observability improvements, alongside model engineering and infrastructure teams.

Wayve · London

Builds and operates the CI/CD infrastructure underpinning Wayve's software development lifecycle, maintaining pipelines, build agents, runners and artifact storage. Works with engineering teams to cut build and test feedback times, improving caching, dependency management and reproducible builds. Also develops self-service tooling and automation for pipeline management.

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

Builds virtual vehicle models using physics-based and data-driven techniques, validating them against on-road data and converting them into efficient software components. Runs track and partner experiments to improve model accuracy, and integrates models into simulation, hardware-in-the-loop and correlation pipelines across robotics, simulation and product teams.

Wayve · London

Owns end-to-end supply chain execution across assigned programmes and product builds, covering prototype development, new product introduction and fleet launches. Acts as the primary supply chain lead and strategic liaison between hardware engineering and procurement, managing BOM translation, long-lead items, upfitter and partner relationships, and KPI reporting. Combines strategic programme ownership with hands-on execution in a fast-moving hardware environment.

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

Develops, tunes and validates trajectory-generation and motion-control algorithms that translate the AI Driver's outputs into safe, smooth vehicle motion across ADAS and AV platforms. Writes latency-sensitive, production-quality C++ control software and uses simulation, closed-loop evaluation and on-road testing to characterise controller behaviour and diagnose issues.