Robotics Jobs

• London
• On-site
• Mid-level
• Permanent

Design and integrate mechanical solutions for sensors and compute across multiple vehicle platforms, owning trade-offs across performance, cost, manufacturability and serviceability. Build test rigs, jigs and fixtures, produce 2D drawings, assemblies and BOMs with GD&T, and work hands-on with suppliers and cross-functional electronics teams.

SolidWorks · SolidWorks PDM

• London
• Hybrid
• Senior · manages people
• Permanent

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.

Flyte · Airflow · Dagster +6

• London
• Hybrid
• Permanent

Develop, integrate and tune trajectory-generation and motion-control algorithms that turn AI Driver outputs into safe, smooth vehicle actuation across multiple platforms. Own production-quality, latency-sensitive C++ control software, using simulation, closed-loop evaluation and on-road testing to validate performance and safety.

CAN

• London
• Hybrid
• Senior
• Permanent

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.

PyTorch · TensorRT · GitHub Actions +1

• London
• Hybrid
• Senior
• Permanent

Build and operate a globally distributed Data Transfer Hub moving petabytes of sensor data per day from partners like Uber, Stellantis and Nissan. You'll design parallelised pipelines in Python and Terraform using Flyte, Kafka and Azure, own production reliability and observability, and join an out-of-hours on-call rotation.

Flyte · Kafka · Azure +4

• London
• Hybrid
• Mid-level · manages people
• Permanent

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.

QNX · OpenTelemetry · Grafana +7

• 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

• London
• Remote
• Lead
• Permanent

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.

HMI

• London
• Hybrid
• Senior
• Permanent

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.

NVIDIA Nsight · Lumos · tegrastat +5

• London
• Hybrid
• Senior
• Permanent

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.

• London
• Hybrid
• Mid-level
• Permanent

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.

Kubernetes · MCP · RAG

• London
• Hybrid
• Permanent

Builds Python services and microservices that orchestrate the end-to-end model-release workflow, integrating feature candidates into release branches and automating readiness checks before training. Connects training platforms, simulation and on-road testing, surfacing quality gates and approvals, and productionises services on Azure and Kubernetes with strong observability.

Azure · Kubernetes · React +1

• London
• Hybrid
• Mid-level
• Permanent

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.

GenAI Development Tools

• London
• Hybrid
• Lead · manages people
• Permanent

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.

Python · PyTorch · GAIA +2