Machine Learning Jobs

• London
• Hybrid
• Lead
• Permanent

Lead the technical strategy, architecture and deployment of secure AI systems across high-stakes domains, bridging research and production. You'll set engineering standards for safe ML deployment, build scalable cloud infrastructure and multi-agent tooling, and partner with Frontier Labs on safety evaluations. The role also involves advising senior client stakeholders and mentoring engineering talent.

AWS · Azure · GCP +4

• London
• Hybrid
• Lead
• Permanent

Lead technical strategy, architecture and deployment of secure AI systems across high-stakes domains, bridging AI research and production. You'll build scalable ML infrastructure, champion safety-first frameworks and capability evaluations, advise senior client leadership, and mentor engineering talent while partnering with Frontier Labs on multi-agent tooling and AI governance.

AWS · Azure · GCP +4

• United Kingdom
• Remote
• Permanent

Builds agents that run real parts of the business, working in Marketing Engineering and forward-deployed to growth pods to find problems and own solutions end to end. Uses Python, SQL, LLM APIs and agent orchestration with frontier models, focusing on making agents reliable, measurable and safe enough for the business to depend on.

LLM APIs

• United Kingdom
• Remote
• Permanent

Backend-leaning full-stack role building and maintaining a platform on top of cutting-edge voice models used by millions, adding product functionality and integrations, and strengthening internal infrastructure for scale, performance and security. Engineers collaborate with Frontend, Growth and Sales teams, with flexible project staffing across the company.

Kubernetes · Stripe

• London
• Senior
• Permanent

Design and implement generative models that learn intervention effects from single-cell perturbation and multiomic data, focusing on counterfactual prediction and experimental design. Work in interdisciplinary teams with experimental biologists to validate computational hypotheses and guide the highest-signal next experiments, using modern ML tooling and scalable infrastructure.

• London
• Senior
• Permanent

Processes and QC's paired single-cell RNA-seq and scATAC-seq at scale, building Nextflow pipelines and multimodal training datasets in Zarr for GPU-accelerated model training. Partners with wet lab scientists and ML modellers, contributing to evaluation frameworks that test whether models capture meaningful biology.

STARsolo · Alevin-fry · Chromap +7

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

Join the model performance and scaling team to implement and optimize LLM post-training methods on frontier models, working with research teams to turn new methods into production systems. The role focuses on distributed training and inference performance, low-precision methods, and frameworks like JAX or PyTorch, in a hybrid London setting.

JAX · PyTorch · NCCL +5

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

Own, secure and scale a suite of self-hosted, multi-user vendor applications across cloud environments. Day to day you build Kubernetes deployment pipelines, maintain Terraform IaC, run container and dependency security scanning, remediate CVEs, and configure SSO/RBAC via SAML 2.0 and OIDC, bridging integration, operations and security.

Kubernetes · GitHub Actions · GitLab CI +7

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

Builds and scales the infrastructure that trains and deploys OpenAI's agentic models, spanning a novel in-house container orchestration platform, FastAPI and gRPC APIs, and Terraform-managed cloud systems. Works closely with researchers on novel training runs while scaling production agent platforms to hundreds of millions of users.

Kubernetes · FastAPI · gRPC +7

• London
• Remote
• Lead
• Permanent

Own 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. Define the vehicle–operator contract, fallback/MRM behaviour and latency budgets, and drive cross-org execution across autonomy, safety, platform and product teams feeding into the L4 safety case.

HMI

• London
• On-site
• £130,000 – £180,000 pa
• Director · manages people
• Permanent

Lead the entire AI research strategy for a financial crime intelligence business, building and managing a team of researchers and ML engineers while staying hands-on. Drive LLM fine-tuning, agentic systems, vision models, evaluation frameworks and explainability standards for highly regulated AML, compliance and fraud detection use cases, taking research from concept to production.

LLMs

• London
• Remote
• £80,000 – £95,000 pa
• Senior
• Permanent

Hands-on senior role in a newly formed team building applied Generative AI products for synthetic data generation and augmentation. You will design, validate and productionise LLM-based solutions, working closely with Product and Engineering, and communicate methodology to non-technical stakeholders. High autonomy and end-to-end ownership from problem definition to delivery.

RAG

• London
• Remote
• Entry level
• Temporary

A four-month, full-time research fellowship focused on empirical AI safety and security projects, using external infrastructure like open-source models and public APIs. Fellows receive direct mentorship from Anthropic researchers, join a shared workspace or work remotely, and aim to produce a public output such as a paper submission.

Large Language Models · Deep Learning Frameworks

• London
• Senior

Own end-to-end design for a major area of the Databricks platform, spanning data engineering, analytics, databases, apps and AI agents. Work ranges from framing and interaction models to visual polish, with heavy use of interactive prototypes and AI coding agents to ship changes directly in the codebase alongside engineers. Designers also set quality bars, run customer research, and build reusable UX patterns and design system components.

Databricks · AI Coding Agents · Genie +5

• London
• Hybrid
• Permanent

Builds ground-truth datasets and computer vision classifiers that describe complex driving scenes, spanning road geometry, spatial relationships, road users and driving behaviour. Works with internal customers to define annotation tasks and acceptance criteria, curates datasets, and integrates classifiers with enrichment infrastructure for corpus analysis and scenario mining.

PyTorch · SQL