Artificial Intelligence Jobs

Faculty · London

Leads a small, high-agency research team setting the scientific agenda for AI safety, with a focus on large language models and safety-critical systems. Involves conducting and overseeing red-teaming and evaluations in high-risk domains such as CBRN and cybersecurity, publishing at top conferences, and mentoring researchers while aligning work with commercial goals.

Faculty · London

Conducts original technical research in AI safety, designing experiments to study and steer transformer-based LLM behaviour using white-box and black-box interpretability methods. Builds reproducible research code and tooling in Python and PyTorch, and communicates findings to frontier labs, government bodies and safety institutes. Works alongside senior and lead scientists, with part-time hours open to discussion.

Carrington Recruitment Solutions · Birmingham · £80,000 – £90,000 pa

Hands-on full stack lead role guiding a small development team across a portfolio of applications, setting engineering standards while collaborating with Product, Architecture and wider technical groups. Tech stack spans C#, .NET, Python, Azure PaaS (Functions, Logic Apps, Cosmos DB, App Service, ARM/Bicep), SharePoint and React, with an AI edge and GenAI exposure welcome. Mainly remote with occasional Birmingham office visits and light travel to other offices.

Carrington Recruitment Solutions · Sheffield · £80,000 – £90,000 pa

Hands-on full stack lead role guiding a small development team across a portfolio of applications, setting engineering standards while collaborating with Product, Architecture and wider technical groups. Work spans C#, .NET, Python, Azure PaaS, SharePoint and React, with an AI edge including GenAI tooling and taking experiments through to production-grade solutions.

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.

Capital One · Mansfield

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. Set technical direction, manage projects, communicate with stakeholders and mentor junior team members, taking ideas from prototype to production.

Capital One · Nottingham

Leads development of proprietary deep learning models to enhance underwriting capabilities, building neural networks such as LSTMs, RNNs and Transformers on structured and unstructured data. Bridges R&D and production, prioritising initiatives with stakeholders and mentoring junior team members.

Harnham - Data and Analytics Recruitment · United States · US$200,000 – US$225,000 pa

Build and own core platform capabilities including application infrastructure, APIs and shared services, developing full stack applications in Python, React and TypeScript. Surface machine learning and predictive analytics insights through intuitive interfaces and integrate AI/LLM workflows into production, working in a small innovation team with significant architectural ownership.

Thought Machine · Singapore

Provides 24/7 global client support for a cloud-native core banking platform, triaging technical issues, reviewing logs, traces and observability dashboards, and performing initial diagnostics. Also provisions cloud infrastructure, runs product upgrades and releases, and works with L3 engineering and client success teams on root cause analysis.

eFinancialCareers · London · £450 – £550 pd

Develops and maintains C# software and algorithms that process incoming news streams, turning financial and market data into accessible information for research and investment decisions. Also explores artificial intelligence to enhance information processing and contributes to the wider software infrastructure supporting Global Research services. Works alongside Python-based tooling within a consultancy team serving financial services clients.

Reed · Cambridge

Lead statistical and bioinformatics analysis projects, developing computational algorithms and applying machine learning to functional genomics research. Work with NGS, OMICS and high-throughput datasets alongside laboratory scientists, using Python, R or Julia and libraries such as TensorFlow and PyTorch. The role also involves mentoring and cross-functional collaboration in a multidisciplinary research team.

eFinancialCareers · Belfast

Hands-on player-manager role leading a growing Data & Analytics function, combining Power BI development, SQL analysis and AI exploration with stakeholder management and delivery leadership. You will build dashboards and semantic models, manage the Power BI environment and backlog, prototype HTML-based analytical applications, and apply generative AI and Copilot to improve reporting while coaching analysts and engineers.

Isomorphic Labs · Cambridge, United States

Lead DMPK strategy across drug discovery projects, designing screening cascades and mechanistic experiments while integrating PK, PD and toxicology data for dose and safety predictions. Work within an AI-first preclinical team, shaping ADME predictive models and authoring regulatory documents to advance candidates toward first-in-human trials.

Isomorphic Labs · Cambridge, United States

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

PhysicsX · New York, United States · US$150,000 – US$190,000 pa

Delivery-focused role embedding physics-aware AI models into customer tools, working on-site with clients across aerospace, automotive and energy. Involves building reliable ML data pipelines, manipulating 3D point-cloud and mesh data, and translating R&D outputs into reusable libraries and products. Expects travel of 3-4 weeks per quarter to customer sites worldwide.