Artificial Intelligence Jobs

Faculty · London

Lead the design, build and deployment of production-grade ML and LLM systems for national security and AI safety clients, including capability testing of frontier models. Act as a trusted technical advisor, define engineering standards for ML at scale, and mentor junior engineers while working with frontier labs on red teaming and evaluation.

Faculty · London

Lead the design, build and deployment of production-grade ML and software systems for clients across pharma, academia and MedTech. The role blends hands-on Python and cloud engineering with architecture decisions, client-facing advisory work and mentoring junior engineers. It sits within a cross-functional life sciences team focused on AI for therapy research and commercialisation.

Michael Page Technology · London · £62,000 – £75,000 pa

A brand new AI Engineer role within a 20-person AI team in the financial sector, designing and deploying production-scale GenAI and machine learning solutions. Day to day involves building scalable AI models, integrating AI into existing systems, analysing large datasets, and collaborating with cross-functional teams and stakeholders. The tech stack centres on Azure services and Python or C#.

ElevenLabs · United Kingdom

Owns the path from research checkpoint to production serving infrastructure, optimising inference latency, throughput and cost using quantization, distillation, KV-cache optimisation, batching and custom kernels. Builds high-performance serving systems for real-time streaming workloads and tooling that lets researchers ship models quickly and safely.

Rise Technical Recruitment · London · £90,000 – £120,000 pa

Design and build full-stack AI-powered product features, working across front-end, back-end, AI and infrastructure. Develop and optimise LLM, computer vision and agent-based systems, plus evaluation, prompt engineering and fine-tuning frameworks. High-ownership role shaping product direction and AI strategy in a scaling financial crime prevention start-up.

Scale AI · London

Builds and deploys end-to-end AI applications for public sector clients, from custom datasets and evaluation pipelines to fine-tuned and agentic models in production. Works closely with client stakeholders, data annotation specialists and cross-functional teams, with occasional travel of about two weeks per quarter.

ARM · Dublin, Ireland

Lead the architecture, deployment and operation of a large-scale AI/ML platform spanning conventional ML and agentic AI, owning the roadmap and engineering standards. Hands-on role covering MLOps/LLMOps, CI/CD, IaC, Azure infrastructure and multi-agent orchestration frameworks, while mentoring engineers and acting as senior escalation point.

Maxwell Bond · London · £150,000 – £175,000 pa

Hands-on role building LLM agent and retrieval systems on a small UK core team, reporting to the Head of Engineering. Work spans LangGraph/LangChain workflows, RAG pipelines with Qdrant and GraphRAG on Neo4j, model integration across Anthropic, OpenAI and Bedrock, plus evaluation harnesses and observability. Token cost, latency and auditability are treated as engineering constraints throughout.

Causaly · London

Design and ship ML/AI solutions end-to-end, from data exploration to deployment and monitoring, choosing between classical ML, NLP, LLM and agentic approaches. Work closely with product, design and engineering on user-facing AI features, champion model and data quality, and mentor junior engineers in a biomedical knowledge platform team.

Anthropic · London · £255,000 – £325,000 pa

Lead a London-based team building connectivity infrastructure for Claude, including the MCP proxy, OAuth and token management, and admin controls. Partner with San Francisco leadership across claude.ai, Claude Code, Cowork and the API, owning reliability, on-call and incident response for systems external partners depend on.

Databricks · London

Lead a delivery team of 8+ engineers building and productionising data and AI solutions on the Databricks platform for enterprise customers. The role blends hands-on technical oversight of Spark, Python/Scala, cloud and MLOps architectures with professional services delivery metrics, hiring and coaching. Hybrid working in London, with accountability for bookings, revenue, margin and customer satisfaction.

Ncounter · Reading · £120,000 – £140,000 pa

Hands-on engineering leadership role in a technology consultancy serving National Security & Defence, blending people management with technical ownership. You'll lead a multidisciplinary software, platform and DevOps team, define architecture and standards across cloud-native, AI/ML and MLOps platforms, and oversee production delivery into customer environments. Distinct for requiring SC or DV clearance and defence experience while remaining close to the technology.

PhysicsX · New York, United States

Lead the ML approach to manufacturing and MRO data, taking models from design through deployment in customer production environments across cloud, on-prem and edge. Work with sparse, drifting sensor and process data, fusing physics simulation with shop-floor measurement, and set uncertainty quantification and validation standards. Mentor engineers and data scientists while travelling to customer sites roughly 3-4 weeks per quarter.

PhysicsX · Singapore

Develops high-fidelity multiphase CFD and DEM models for industrial bioprocess and chemical engineering applications, covering gas-liquid, solid-liquid, VOF and Euler-Euler/Euler-Lagrange approaches. Owns the full simulation pipeline from geometry clean-up and meshing to solver setup, HPC job scheduling and experimental validation, while building parametric CAD models and AI surrogate models to support design optimisation and customer-facing delivery.

Databricks · London

Customer-facing role building and productionising data and AI solutions on the Databricks platform, owning architecture and design decisions for end-to-end systems spanning data engineering, ML/AI and application development. Embeds with client teams from engineers to executives, delivering production-grade reference architectures and reusable accelerators, with around 20% travel.