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.

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.

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.

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.

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.

Harnham - Data and Analytics Recruitment · London · £40,000 – £50,000 pa

Analyses large, complex datasets to uncover business insights while supporting data pipeline development and engineering processes. Works with proprietary client data on Generative AI and LLM projects, including data labelling, model training and experimentation, collaborating closely with founders in an early-stage AI startup.

PhysicsX · Singapore

Lead technical delivery of physics-informed AI, architecting deep learning models and optimisation methods to predict and control physical systems. Own data pipelines and pre-processing best practices while mentoring a team and collaborating with simulation engineers and customers. Involves frequent on-site customer travel across multiple regions.

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.

CrowdStrike · United Kingdom

Lead a team of three data scientists at the intersection of machine learning, big data and cybersecurity, setting technical standards and driving strategy for threat detection and agentic AI systems. Work spans research through production deployment, using CrowdStrike's large-scale behavioural and malware data, while mentoring the team and partnering with security research, engineering and product.

CrowdStrike · Spain

Leads a team of three data scientists building machine learning and agentic AI systems for threat detection, malware analysis and security automation. Owns technical strategy, roadmaps and production deployment while mentoring staff and partnering with security research, engineering and product teams.

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.

NVIDIA · Bristol

Research and develop techniques to GPU-accelerate leading high performance computing applications across scientific computing, computational engineering and data science. The intern performs in-depth analysis and optimisation for current and next-generation GPU architectures, working with application developers and collaborating with architecture, research, libraries, tools and system software teams.