Robotics Jobs in London

• London
• On-site
• Lead · manages people
• Permanent

Hands-on engineering lead owning the path from AI agent task to healthy deployed change, building secure reproducible agent runtimes, verification tooling, and developer interfaces. Recruits and leads a new developer productivity team while working across Developer Tools, Security, Simulation, and robot software to cut cost and review time per accepted change.

Kubernetes · Linux

• London
• On-site
• Senior
• Permanent

Develops learning-based locomotion and whole-body control policies for humanoid robots, using reinforcement and imitation learning, generative models and motion primitives. Builds scalable simulation and training pipelines in Isaac Lab and MuJoCo, and deploys, debugs and fine-tunes policies on physical robots, tackling sim-to-real transfer and real-time inference latency.

Isaac Lab · Isaac Sim · MuJoCo +1

• London
• Hybrid
• Lead
• Permanent

Owns end-to-end system architecture for the Wayve AI Driver across L0–L4, defining interface contracts, ECU and sensor requirements, and safety mechanisms. Leads technical alignment with OEMs, Tier 1s and partners, and supports integration, bring-up and system-level debugging on vehicles and HiL/ViL benches.

Linux · RTOS · HMI +3

• London
• Hybrid
• Senior
• Permanent

Owns embedded software that connects an autonomous driving AI to vehicle platforms, building integration and adaptation layers across hardware. Works on inference integration, vehicle data, navigation, localisation and motion control interfaces, taking features from design through HIL and vehicle testing. Requires strong modern C++ and Linux/QNX experience, ideally on Nvidia and Qualcomm platforms.

Nvidia · Qualcomm · Linux +3

• London
• Hybrid
• Senior
• Permanent

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.

Linux

• London
• Hybrid
• Mid-level
• Permanent

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.

• London
• Hybrid
• Senior
• Permanent

Sets technical direction for petabyte-scale object storage powering autonomous driving AI, leading a multi-quarter programme from architecture to adoption. Builds production services and controllers in Python or Go with Kubernetes and Terraform, working with ML, data, security and privacy teams on retention, caching, replication and cost reduction.

Kubernetes · Terraform · Azure Blob Storage +4

• London
• Hybrid
• Mid-level
• Permanent

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.

PyTorch · TensorFlow · Azure +1

• London
• Hybrid
• Permanent

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.

Flyte · Airflow · Dagster +6

• London
• Hybrid
• Senior
• Permanent

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.

PyTorch · GAIA

• London
• Hybrid
• Permanent

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.

Dymola · CarSim · CarMaker

• London
• Hybrid
• Senior
• Permanent

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.

Python · SQL

• London
• Hybrid
• Director
• Permanent

Owns the architecture, strategy and integrity of safety cases for robotaxi and OEM ADAS products, defining top-level claims, argumentation structures and evidence traceability. Sits independently from Engineering and Product, providing senior expert challenge and assurance oversight across AI/ML, systems, validation and operational safety.

ISO 26262 · ISO 21448 · ISO/PAS 8800 +2