Artificial Intelligence Jobs in London

Wayve · London

Lead the technical architecture and roadmap for onboard localisation, designing and productionising state-estimation systems that fuse GNSS, IMU and wheel odometry for accurate vehicle pose estimates. The role spans algorithm design, prototyping, validation and deployment on real-time vehicle platforms, with hands-on technical leadership and mentorship across robotics, calibration, controls and sensor teams.

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, compiler/runtime behaviour and kernel execution, 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

Train, debug and improve computer vision and 3D perception models for driver assistance, working across the full ML lifecycle from data and training to evaluation and iteration. The role spans latency-constrained on-car perception and large-scale offline work with lidar, maps and 3D reconstruction to build auto-labelling data flywheels.

Wayve · London

You'll define and manage the technical architecture for integrating Wayve's AI Driver into OEM and Tier 1 vehicle platforms, covering software–vehicle interfaces, sensors, middleware, ECUs, timing, diagnostics and validation. The role sits between core AI architecture and customer programs, turning ambiguous requirements into interface contracts, ownership boundaries and verifiable specifications.

Wayve · London

Lead large-scale data enrichment and curation for the Core Model Safety team, mining hard and rare events and building workflows across pre/mid-training, reward modelling and self-supervised labelling. Design and train out-of-distribution detection mechanisms for robust driverless operation, working at the intersection of model engineering, infrastructure, compute and data.

Wayve · London

Owns reliability of large-scale GPU, Kubernetes and distributed AI training infrastructure, turning recurring operational problems into durable engineering solutions. Improves observability, automation, deployment safety, capacity planning and incident learning, and builds GitOps delivery with Argo CD or Flux. Works across AI Platform, Compute & Data Platform and Cloud Infrastructure teams.

Wayve · London

Develop next-generation generative world models and planners such as GAIA, simulating complex driving environments for faster training and scalable deployment. Work spans diffusion and transformer architectures, latent compression, context pruning and inference-latency optimisation, with closed-loop agent interaction and sim-to-real evaluation. The role combines ML research, multi-modal modelling and production deployment, including mentoring and publishing.

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-based data analysis, spanning simulated and physical test environments. Open at senior IC or manager level, with close collaboration across Product, Safety and Release stakeholders.

Wayve · London

Lead functional safety activities for an end-to-end autonomous 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 to support certification.

Wayve · London

Build and operate a globally distributed Data Transfer Hub moving petabytes of video, LiDAR and sensor data per day between Wayve and partners such as Uber, Stellantis and Nissan. Write pipeline logic in Python, manage infrastructure with Terraform, and use Flyte, Kafka and Azure for orchestration, event-driven lifecycle tracking and storage. The small, high-autonomy team owns production reliability, observability and cost efficiency, with an out-of-hours on-call rotation once the service is established.

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 and builds CI/CD tooling and observability to deliver ML systems reliably at scale.

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 and 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 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.