Artificial Intelligence Jobs in London

Isomorphic Labs · London

Lead and contribute to core machine learning research applying large language models to drug discovery, developing and refining LLM-driven approaches across biology and chemistry problems. Work spans post-training, reasoning, test-time scaling, tool-use, alignment, agents, reinforcement learning and fine-tuning, with model training and inference engineering at scale. Interdisciplinary collaboration with research scientists and engineers, plus technical mentorship and project leadership depending on experience.

Isomorphic Labs · London

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 and domain experts, with opportunities to lead projects and mentor others depending on experience.

OpenAI · London

Builds data-intensive, AI-powered applications and infrastructure that help operators and investigators detect, triage and review high-severity harm, working across UIs, services and pipelines. Partners closely with the Child Safety team and cross-functional groups, owning systems end-to-end in an ambiguous, fast-moving environment. Involves exposure to sensitive and egregious content.

King's College London · London · £45,031 – £52,514 pa

Designs, builds and evaluates AI-enabled evidence synthesis tools and pipelines for the METIUS programme, writing production-quality Python code and onboarding consortium partners. Runs methodological and evaluation studies on the reliability and usability of AI-assisted synthesis methods, publishing the results, and contributes to the Solace-AI project on climate-health emergencies. Works alongside software developers, data scientists and evidence synthesis specialists.

King's College London · London · £53,947 – £63,350 pa

Combines education, research and academic citizenship, co-leading an Introduction to Digital Health module and coordinating a new Master of Digital Health launching in 2027. Develops an independent research programme in digital health and responsible AI, supervising Master's dissertations and building interdisciplinary collaborations across King's, the NHS and industry.

eFinancialCareers · London

Lead a small, high-performing team of 6-7 engineers owning core ML infrastructure, including distributed model training, LLM hosting and fine-tuning, and scalable deployment systems. The role combines hands-on technical direction with people leadership, integrating advanced ML capabilities into production-grade, high-stakes systems. Suited to experienced engineering managers, not first-time managers.

VIQU IT · London · £75,000 – £80,000 pa

Designs and deploys AI/ML models for forecasting, propensity, churn and customer segmentation, owning end-to-end workflows from feature creation to ML Ops deployment and monitoring. Works hands-on across multiple products, architecting bespoke datasets and coaching junior data scientists in a cloud-native, AI-first SaaS team.

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.

Databricks · London

Customer-facing, billable engineering role owning architecture and design decisions while building production-grade data and AI systems on the Databricks platform. Involves embedding with client teams, integrating with their systems, and delivering end-to-end pipelines, ML/AI models and user-facing applications, with around 20% travel to customer sites.

Experis · London · £450 – £500 pd

Delivery-focused project manager supporting a computer vision AI capability, working across the client, a UK development contractor and wider stakeholders. Responsibilities cover governance, progress and risk reporting, cost and dependency visibility, and resource prioritisation in a fast-moving, stakeholder-heavy environment with evolving AI requirements.

NXA Talent LTD · London · £500 pd

Design and build agentic AI systems with multi-step reasoning, multi-agent orchestration and scalable AI microservices in Python and Azure OpenAI. Develop RAG architectures, vector search and orchestration workflows using Semantic Kernel and LangGraph, integrating enterprise systems via MCP. The role also covers AI governance, safety and deploying LLM services into production within a large retail environment.

Vallum Associates · London · £475 – £500 pd

Data scientist role focused on collecting and analysing large datasets, building experimental models and machine learning applications in Python, and performing complex statistical analysis. Involves leading small teams on data science products, developing classical ML and LLM solutions with prompt and RAG techniques, and mentoring junior data scientists. Hybrid working with two days per week in the London office.

OpenAI · London

Backend engineering role building and operating the distributed systems behind ChatGPT at significant scale. You'll write production code, design shared services and APIs, lead infrastructure migrations, and own production behaviour through monitoring, staged rollouts and incident response. Combines backend development with reliability and on-call work, closely partnered with product teams.

Harnham - Data and Analytics Recruitment · London · £100,000 – £140,000 pa

Build and lead multimodal AI applications spanning text, audio and video, including AI-generated avatars and automated content summarisation, within a growing AI team in a mature data function. The role involves translating business needs into scalable, production-deployed AI products and collaborating with a multidisciplinary team, with technical leadership duties at Lead level.

eFinancialCareers · London

Design and build AI-powered tools, automations and integrations using Python, PowerShell and APIs, exploring Agentic AI and LLM use cases across internal business functions. Advise on embedding AI into enterprise architecture within a regulated investment management environment, working with engineering, product and business teams. Distinct for its focus on engineering productivity and architecture strategy rather than traditional ML modelling.