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.

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.

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.

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.

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 · £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 · 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.

Morson Edge · Heathrow, United States · £625 – £650 pd

Lead data and AI engineering work for a major airline, focused on AWS, Snowflake and CI/CD pipelines. The role is inside IR35 and requires one to two days per week on-site at Heathrow, with the remainder likely remote. It is a long-term contract position.

Morson Edge · West Yorkshire · £170,000 – £180,000 pa

A senior leadership role owning the data and AI strategy, roadmap and technical direction across the organisation. Day to day it spans hands-on work with generative AI, LLMs, RAG and agentic architectures, MLOps and data platform governance, plus building and leading a high-performing Data & AI team and partnering with Product, Engineering, Architecture and Security to scale prototypes into production.

eFinancialCareers · London

Leads a global legal and professional services firm's AI and data agenda, translating strategy into a delivery programme that moves initiatives from experimentation to sustainable adoption. Works across legal, fiduciary and business services divisions on productivity, decision-making and client outcomes, reporting to the Director of Service Innovation and managing AI and data delivery teams through matrix leadership.

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.

Wayve · London

Owns the data strategy behind an end-to-end autonomous driving AI platform, spanning the full learning cycle from foundation model training to production programmes. Leads a multidisciplinary data organisation, deciding what data matters and building the flywheel from real-world signals through discovery, curation and enrichment. Focuses on finding rare, safety-critical scenarios in very large datasets using embeddings, semantic search and model-driven selection.

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.