Artificial Intelligence Jobs in London

PhysicsX · Singapore

Lead the deployment of ML models and engineering surrogates—deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, and optimisation—into customer production environments. Own scoping, architecture, and success metrics for data/ML systems built with Python, PyTorch, Pandas, fastAPI, Scipy, and Kubeflow across cloud and on-prem. Mentor engineers and data scientists while travelling 3-4 weeks per quarter to customer sites worldwide.

PhysicsX · Singapore

Customer-facing engineering role building and deploying applications that put physics AI models into production for industrial clients. You will work directly with customers, data scientists and ML engineers, prototyping tools, iterating on user feedback, and building Python FastAPI microservices deployed on Kubernetes, Terraform and AWS/Azure.

Wayve · London

Develops embedded software connecting an AI Driver to vehicle steering, braking and propulsion systems, working hands-on with benches and vehicles. Involves MATLAB/Simulink development, drive-by-wire actuation logic, CAN/CAN-FD diagnostics, OTA updates and ADAS/HMI interfaces, collaborating with OEMs, suppliers and controls engineers.

Wayve · London

Owns the data strategy behind an end-to-end autonomous driving AI platform, spanning the full learning cycle from foundation model training to production programmes. Leads a multidisciplinary data organisation, deciding what data matters and building the flywheel from real-world signals through discovery, curation and enrichment. Focuses on finding rare, safety-critical scenarios in very large datasets using embeddings, semantic search and model-driven selection.

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

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.

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

Cross-organisational individual contributor defining software architecture as Wayve scales its AI Driver across vehicle platforms, OEM programmes and Robotaxi. Works at the intersection of AI, robotics, computer vision, simulation, training and inference, onboard software and product engineering, setting boundaries, interfaces and abstractions and leading large architectural changes across teams.

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, hire and grow data scientists, and build tooling to scale the team's capability.

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

Owns the technical architecture and roadmap for LiDAR and cross-sensor 3D sensing, developing calibration, registration, temporal alignment and motion compensation methods. Blends algorithm research with production deployment in C++/Python, providing technical leadership and mentorship across the 3D sensing stack.