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 · £55,000 – £65,000 pa

Mid-level data scientist role focused on fraud detection and mitigation, working across the full data science lifecycle. Responsibilities include processing large datasets, building and maintaining fraud detection, identity resolution and predictive machine learning models, evaluating new data sources, and monitoring model performance. Requires Python, SQL and production deployment experience, collaborating with data, technology, risk and product teams.

Michael Page · Leeds · £40,000 – £48,000 pa

Analyse large datasets to uncover trends and build predictive models and algorithms that support strategic decisions in a financial services setting. Work within a collaborative analytics team, presenting findings to non-technical stakeholders and helping maintain data pipelines and infrastructure. Requires Python, R or SQL plus statistical and machine learning techniques, with GIS tooling also desirable.

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.

CrowdStrike · Spain

Analyzes large-scale security telemetry, threat intelligence feeds and detection data to surface trends, anomalies and emerging threats. Builds dashboards, data pipelines and KPI frameworks using SQL, Python, Logscale and visualization tools, working cross-functionally with product and engineering teams in the Office of Adversary Strategy.

CrowdStrike · Romania

Analyzes large-scale security telemetry, threat intelligence feeds and detection data to surface trends, anomalies and emerging threats. Builds dashboards, reports and data pipelines using SQL, Python, Logscale and graph databases, working cross-functionally with product and engineering teams to turn raw security data into actionable insights and KPIs.

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.

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.

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.

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 Glasgow · Glasgow · £50,253 – £58,225 pa

Develops physics-informed machine learning and uncertainty quantification methods to improve subsurface characterisation for offshore wind and net-zero infrastructure. Joins an interdisciplinary team of engineers, data scientists and geophysicists within a UKRI-funded Fellowship, with scope to shape an ambitious research programme.