Robotics Jobs

• 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
• 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
• 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
• Lead
• Permanent

Lead an ambitious research agenda at the intersection of LLMs, VLMs, VLAs and embodied AI, exploring how world knowledge, memory and reasoning improve physical-world decision-making. Stay hands-on developing architectures, training and post-training large-scale models, while mentoring researchers and shaping technical direction across London and Sunnyvale.

PyTorch

• London
• Hybrid
• Senior
• Permanent

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.

GAIA · GPU · KV Cache

• London
• Hybrid
• Lead
• Permanent

Lead the technical direction for an offline 3D reconstruction system that turns raw vehicle sensor data into quality-assessed 3D ground-truth geometry and ego motion. The role spans SLAM, lidar point-cloud registration, state estimation and sensor fusion, with responsibility for architecture, roadmaps, prototypes and cross-functional alignment across perception, calibration and validation teams.

ROS · PCL · OpenCV +3

• London
• Hybrid
• Lead
• Permanent

Owns the autonomy performance measurement framework for a public-scale robotaxi deployment, defining metrics, dashboards and release gates for an end-to-end learned driving system with no existing playbook. Runs the performance improvement loop across model, robot software, backend and evaluation tooling, leading cross-functional execution without direct reporting authority while staying hands-on in Python, C++ and SQL.

Databricks · Looker · Grafana +1

• London
• Hybrid
• Lead
• Permanent

A cross-functional individual contributor role shaping software architecture across onboard software, AI, simulation, training, inference and Robotaxi systems. The architect defines boundaries, interfaces and abstractions spanning AI, compute and vehicle platforms, leading large multi-team architectural changes and acting as a technical decision-maker on safety-critical systems.

• 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
• Senior
• Permanent

Builds high-quality Python libraries and platform tooling for multimodal data loading, distributed training, inference, checkpointing and observability, supporting thousands of GPUs. Partners closely with ML teams to turn complex requirements into stable, reusable abstractions and clear APIs, leading projects end to end while raising engineering standards.

PyTorch · TensorFlow · Azure +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
• 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.

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