Machine Learning Jobs

• 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
• Mid-level · manages people
• Permanent

Lead a London-based team building the on-vehicle experiment platform that lets researchers deploy driving models to vehicles, run experiments and collect training data. You own people, roadmap and OEM partner relationships while staying hands-on with embedded Linux, C++/Python and over-the-air deployment across vehicle fleets.

NVIDIA Jetson · NVIDIA DRIVE · QNX +4

• Cambridge, United States
• Hybrid · 3 days in office
• Lead

Lead the safety assessment strategy for small molecule and biologic drug discovery projects from inception to regulatory submission, designing screening cascades and mechanistic experiments. Partner with machine learning researchers to build predictive toxicology models and manage external CROs for all wet-lab data generation, while mentoring junior scientists.

KNIME · Python

• Cambridge, United States
• Hybrid · 3 days in office
• Mid-level

First Technical Program Manager hire for the Drug Design and Medical Research function, supporting small molecule drug discovery programs in Cambridge, MA while integrating with the London office. Responsibilities span program planning, timeline monitoring, risk reporting, budget forecasting and spend tracking, CRO and external partner liaison, and embedding operational processes across teams.

Jira · Confluence

• Loughborough
• Hybrid · 3 days in office
• Lead
• Permanent

Lead the development of proprietary deep learning models to enhance underwriting capabilities, building neural networks such as LSTMs, RNNs and Transformers on structured and unstructured data. The role combines technical direction-setting, stakeholder collaboration and mentoring, taking models from prototype through to production in a hybrid Nottingham-based team.

PyTorch · TensorFlow · Hugging Face Transformers +1

• Leicester
• Hybrid · 3 days in office
• Lead
• Permanent

Leads the development of proprietary deep learning models to enhance underwriting capabilities, building neural networks such as LSTMs, RNNs and Transformers on structured and unstructured data. Sets technical direction, manages projects, communicates with stakeholders and mentors junior team members, driving prototypes through to production.

PyTorch · TensorFlow · Hugging Face Transformers +1

• London
• Hybrid
• Senior
• Permanent

Builds and maintains shared onboard runtime foundations for autonomous vehicles, including application frameworks, communication middleware, lifecycle management, health monitoring and observability. The role focuses on end-to-end latency and performance profiling across OS scheduling, memory hierarchy and compute platforms, with automated benchmarks and CI regression checks. Works closely with engineering teams and middleware suppliers to set shared APIs and architectural direction.

NVIDIA Nsight · Lumos · tegrastat +5

• 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. Works across Model Engineering, MLOps, Measurement, Evaluation, Simulation and Release Management.

Azure · Kubernetes · React +1

• London
• Hybrid
• Permanent

Design, build and operate shared infrastructure for language model access, agent runtimes and observability, taking projects from problem definition through technical design, deployment and ongoing operation. Partner with security, IT and engineering teams, and support adoption through troubleshooting, documentation and reusable patterns.

Kubernetes · MCP · RAG

• London
• Hybrid
• Senior
• Permanent

Set the technical strategy and roadmap for fault detection and fallback systems in an autonomous driving stack, designing and training detection mechanisms that enable safe driverless operation. Lead integration into the shared driving stack, working closely with machine learning, inference optimisation and software engineering partners, and mentor across teams. The role sits in a small, high-impact Core Model Safety team with access to large-scale training and fleet data.

• London
• Hybrid
• Lead · manages people
• Permanent

Lead a team of ML engineers and applied scientists building synthetic data from generative world models like GAIA-3, turning them into a production engine for training-grade driving data. Own the pipeline end to end, from checkpoint and large-scale GPU inference to artefacts landing in driving-model training, while setting technical direction on rig transfer, pose transfer and controllability.

Python · PyTorch · GPU +1

• London
• Hybrid
• Lead · manages people
• Permanent

Builds and leads the technical programme management function for Wayve's AI Platform organisation, owning planning, prioritisation and execution across data and compute infrastructure, developer tooling, training technology and inference optimisation. Coaches a small TPM team, manages cross-team dependencies with ML, research, embedded and vendor partners, and drives measurable gains in developer velocity, compute efficiency and model performance.

Kubernetes · Ray · Flyte +6

• London
• Hybrid · 3 days in office
• Mid-level

Join the Compute Infrastructure team to keep a planet-scale GPU accelerator fleet healthy and efficient. You'll build observability and telemetry pipelines, automate recovery, hunt compute waste, and optimise accelerator utilisation for large-scale training and inference, working closely with ML infrastructure and research teams.

GCP · Kubernetes · Nvidia GPU +1

• London
• Hybrid · 3 days in office
• Lead

Technically lead the Platform group, designing, operating and refining research, development and production cloud infrastructure across GCP, Kubernetes, Docker and Terraform. The role spans core technical decisions, tooling and CI/CD processes, working closely with scientists, ML researchers and product teams, and reports directly to the Director of Engineering.

GCP · Kubernetes · Docker +7

• London
• Hybrid · 3 days in office
• Senior · manages people

Builds greenfield machine learning models and algorithms for drug discovery, designing new architectures, running experiments and scaling training and inference frameworks. Works in an interdisciplinary team of ML scientists, engineers and domain experts, with opportunities to lead projects and mentor others depending on experience.

JAX · PyTorch · TensorFlow +3