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.

Wayve · London

Lead the Applied Methods Data Science team, partnering with the Autonomy organisation to turn experimental and observational analysis of real and simulated driving into evaluations and insights. Set three-, six- and 12-month roadmaps, review technical proposals for statistical rigour, hire and grow data scientists, and build tooling to scale the team's capability.

Barclays · Glasgow · £25,200 pa

A graduate apprenticeship in the technology function, rotating across capabilities to design and build digital solutions, analyse requirements and support delivery teams. Apprentices combine real project work with an AI and Data Science qualification, collaborating cross-functionally with business stakeholders while learning within defined procedures and controls.

Capital One · Loughborough

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 in a hybrid Nottingham team.

Capital One · Lincoln

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. The role involves setting technical direction, mentoring junior team members, and driving prototypes through to production in collaboration with business stakeholders.

Faculty · London

Lead the scientific direction and architectural rigour of upstream AI safety and evaluation standards, partnering directly with Frontier Labs. Design novel experiment frameworks, mentor data scientists, and translate complex challenges into rigorous scientific frameworks for high-stakes client engagements. Combines deep research with commercial strategy and thought leadership.

Faculty · London

Technical leadership role owning delivery of complex machine learning and Generative AI projects for financial services clients, spanning LLM and agentic AI applications. Sets technical direction for the data science team, mentors and manages data scientists, leads bids and scoping, and acts as an external thought leader publishing and presenting at conferences.

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.

dunnhumby · London

Sits within the Insight Enablement function of the Tesco Insights team, shaping enablement strategy and transformation initiatives so Client Success teams can deliver value. Defines propositions and frameworks across products and tools, connects stakeholder needs to business priorities, and champions adoption of AI and emerging technologies.

University of Essex · Ipswich · £40,000 – £45,000 pa

A KTP Associate role embedded at Distag QCS in Ipswich, working with a large, messy ERP dataset never designed for machine learning. The post holder shapes the data, builds reliable models, and leads the introduction of data-driven decision making in a business with no existing in-house data science capability. It blends hands-on Python development with change management, communication and academic paper contributions.

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.

Tech Recruitment Specialists Ltd · London · £38,000 – £45,000 pa

Supports the development, optimisation and deployment of AI and machine learning models, working with large datasets for preprocessing and training, and helping monitor AI applications in production. Collaborates with software engineers, product teams and data specialists, contributes to backend development and API integrations, and researches new AI frameworks. Emphasis on responsible, ethical AI with bias mitigation, transparency and fairness.

NVIDIA · Bristol

Research and develop techniques to GPU-accelerate deep learning, machine learning and other AI workloads, working with technical experts from industry and academia to analyse and optimise complex AI and HPC algorithms on modern CPU and GPU architectures. The intern also publishes optimisation techniques via developer blogs or conferences and helps influence next-generation hardware, software and programming models.

Anthropic · London

Leads multi-hundred megawatt power procurement and energy markets strategy for AI datacentre expansion across multiple EU jurisdictions. Builds relationships with TSOs, DSOs, regulators and ACER, structures PPAs and behind-the-meter solutions, and translates grid constraints into capacity acceleration plans.

Isomorphic Labs · London

Lead formulation strategy for small molecules across drug discovery and preclinical development, designing technologies such as solid dispersions and co-crystals to improve solubility, stability and manufacturability. Interpret stability studies using ICH and ASAP methods, author regulatory submissions, and work with external CROs alongside AI/ML drug design teams.

University of Exeter · Exeter · £21,805 pa

Develops a resource-aware AI framework for 2D and 3D medical imaging that adapts computation to case complexity, clinical risk and available hardware. Investigates where unnecessary computation occurs, builds a configurable model family, and validates it on population-scale abdominal MRI (UK Biobank) and near-patient dermatology imaging, with safety assessed across patient subgroups.