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.

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.

CrowdStrike · Ireland

Lead a team of data scientists working at the intersection of machine learning, large language models and cybersecurity, translating business needs into technical objectives and driving research into production ML systems. The role combines people leadership, roadmap planning and stakeholder communication with hands-on work on malware detection and threat analysis at massive scale.

CrowdStrike · United Kingdom

Lead a team of data scientists applying machine learning, large language models and reverse engineering to cybersecurity problems at massive scale, handling trillions of events daily. The role blends technical leadership, roadmap and stakeholder management with hands-on work on malware detection, threat analysis and AI-driven security automation.

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.

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.

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.

PhysicsX · New York, United States · US$120,000 – US$240,000 pa

Builds and deploys deep learning and probabilistic models to predict and control physical systems, working alongside simulation and ML engineers. Owns data pipelines and production deployment, and collaborates directly with customers on-site across multiple regions. Based in Manhattan with 2-3 days per week in office and frequent travel.

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.

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.

MRJ Recruitment · Manchester · £450 – £525 pd

Builds machine learning models for agentic search, recommendation engines, personalisation and ranking, taking ideas from experimentation into production. Works hands-on with Python, SQL and Snowflake on large datasets, using SHAP for explainability and collaborating with Data, Product and Engineering teams.

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.