Artificial Intelligence Jobs

Hadean · London

Lead a new AI-powered defence product team, line-managing AI/ML, simulation, infrastructure and web engineers while staying hands-on in TypeScript, React and Node. You own delivery end-to-end, hiring and people development, partnering with Product and technical leads, with hybrid working one day a week in Shoreditch.

Harnham - Data and Analytics Recruitment · London · £120,000 – £150,000 pa

Lead and build a data science function within a fintech, owning strategy across risk, affordability and lending decisioning. Design, build and deploy machine learning models using credit risk, Open Banking and customer data, working with Product, Engineering and Credit Risk teams. Requires hands-on Python, SQL and MLOps experience plus credit risk modelling in UK consumer lending.

eFinancialCareers · London

Leads the design, development and operation of high-rigor analytical and machine-learning systems across a complex, regulated financial-services estate, defining the AI/ML roadmap while remaining hands-on. Owns the full model lifecycle from feature engineering and back-testing to deployment, monitoring and incident response, with models expected to be explainable and production-grade. Works closely with engineering, data platform and product teams, mentoring other data scientists with limited line management.

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.

Bowers Partnership · London · £825 pd

Hands-on VP-level data scientist building generative AI, LLM/NLP and statistical modelling products end to end, from prototype to production, for a boutique investment bank's M&A and advisory bankers. Works in a small team, writing production-quality Python and explaining models and assumptions directly to senior non-technical stakeholders. M&A experience is essential; hybrid with at least three days a week in the London W1 office.

Faculty · London

Lead high-impact AI projects for retail and consumer clients, defining data science approaches, designing software architectures, and mentoring colleagues. Own the technical side of client relationships, scope projects, and embed responsible AI practices while delivering bespoke algorithms and production-grade systems.

dunnhumby · London

Joining the Retail Insight team, you will investigate, develop and deploy complex models and algorithms for Tesco, covering personalisation, basket analysis, pricing, promotions and loyalty. The role blends statistical modelling, machine learning and client-facing delivery, building reusable, scalable solutions alongside client leadership teams.

Faculty · London

Lead high-impact AI safety projects for Frontier Labs, inventing novel evaluation frameworks and designing robust software architectures. Mentor technical team members while partnering with commercial teams to scope work and translate complex problems into rigorous frameworks. Requires Python, NumPy, Pandas and ideally evaluation tooling like Inspect AI.

Ocado · London

Owns the software engineering that brings data science and machine learning products into live production for the Autoplanner team, building AI-powered planning systems across global warehouses and last-mile assets. Writes typed, well-tested Python (with some Java for OSP integration), builds APIs and data contracts, manages AWS deployments and CI/CD, and packages, serves and monitors ML models. Acts as engineering partner to data scientists and shares on-call support.

University of Essex · Milton Keynes · £41,950 pa

Develops novel computer vision techniques to capture and analyse live-broadcasted eSports events, identifying in-game events and building low-latency AI calculations for in-play betting markets. Works with Python, TensorFlow or PyTorch alongside Java and .NET colleagues, using historical game data and video feeds to detect irregular play patterns. A KTP partnership between the University of Essex and Sports Information Services Ltd.

Isomorphic Labs · Cambridge, United States

Designs and implements translational strategies for small molecule programmes, overseeing in vitro/in vivo pharmacology, PK/PD and safety studies from early discovery through candidate selection and clinical phase. Manages external CRO networks and acts as the bridge between ML/computational predictions and laboratory validation, with some roles line-managing 2-3 in vivo pharmacologists.

Reperio Human Capital · Dublin, Ireland · £388 – £474 pd

Hands-on engineering role owning AI/ML initiatives end-to-end, from solution design and experimentation through deployment, monitoring and optimisation. Involves building production ML and GenAI solutions including RAG architectures, working with Snowflake and cloud data platforms, and developing Python and R software with strong MLOps, CI/CD and DevSecOps practices. Collaborates with data, product and business teams to turn ambiguous problems into scalable, secure solutions.

Adecco · Cambridge

Lead the AI engineering strategy and delivery of advanced AI products and platforms, reporting to executive leadership. Manage software, platform and AI engineering teams, driving adoption of Agentic AI, LLMs, RAG and multi-agent architectures on Azure, AWS or GCP. Requires a strong engineering background and proven leadership in high-growth environments.

Adecco · Cambridge

Lead the AI engineering strategy and delivery of advanced AI products and platforms, reporting to executive leadership. Manage software, platform and AI engineering teams, driving adoption of Agentic AI, LLMs, RAG and multi-agent architectures across Azure, AWS or GCP. Requires a strong engineering background and proven leadership in high-growth environments.

Wayve · London

Owns the end-to-end release cycle for autonomous-driving AI models, coordinating ML engineering, evaluation, data science, platform, testing and product teams. Defines release gates and promotion criteria from training through validation to fleet deployment, drives regression investigations and rollback decisions, and builds tooling and KPIs to remove bottlenecks in a non-deterministic ML environment.

University of Sheffield · Sheffield · £32,080 pa

Build and evaluate machine learning models that predict Strep A outbreak risk from multiple real-world datasets, turning them into early-warning signals. Work with clinicians and an engineering team so analyses feed into a practical public health tool, with a focus on reproducible Python and/or R analysis.