Artificial Intelligence Jobs

Capital One · Derby

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 combines technical direction-setting, stakeholder collaboration and mentoring, taking ideas from prototype through to production in a hybrid Nottingham-based team.

Capital One · Leicester

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, mentor junior team members and drive prototypes through to production in collaboration with business stakeholders.

Isomorphic Labs · Cambridge, United States

Lead medicinal chemistry on drug discovery projects from initiation to clinical candidate selection, either as Project Lead or Medicinal Chemistry Lead. Partner closely with ML scientists to refine the AI drug design platform, manage CRO resources, and generate IP. Some roles include line managing 2-4 chemists.

Isomorphic Labs · Cambridge, United States

Lead computational drug design programs from initiation through to clinical candidate selection, applying AI-first approaches and shaping the company's ML drug design engine. Work cross-functionally with ML, biology and chemistry teams, with optional people management of 2-3 computational chemists.

Rise Technical Recruitment · London · £90,000 – £120,000 pa

Design and build full-stack AI-powered product features, working across front-end, back-end, AI and infrastructure. Develop and optimise LLM, computer vision and agent-based systems, plus evaluation, prompt engineering and fine-tuning frameworks. High-ownership role shaping product direction and AI strategy in a scaling financial crime prevention start-up.

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.

Ncounter · Manchester · £80,000 – £90,000 pa

Hands-on research engineering role investigating the internal behaviour and security of large language models, turning academic ideas into practical experiments in Python. Work spans model internals, data movement, training risk and safe deployment, alongside production-quality ML engineering, testing and code reviews. Requires active SC clearance and around three days per week on secure sites.

NVIDIA · Switzerland

Develops performance optimizations in deep learning frameworks using JAX, contributing to JAX core components and driving peak performance on NVIDIA hardware. Works with AI researchers to build future-proof models and tooling that bridges numerical computing, simulation and deep learning research. Requires C/C++ and Python skills plus deep knowledge of ML framework internals and CPU/GPU architectures.

NVIDIA · United Kingdom

Develops performance optimizations in deep learning frameworks using JAX, contributing to JAX core components and driving peak performance on NVIDIA hardware. Works with AI researchers to build future-proof models and tooling that bridges numerical computing, simulation and deep learning research. Requires C/C++ and Python, ML framework internals, and CPU/GPU architecture expertise.

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.

Amazon · London

Manage a London-based team of associates producing labelled speech and language data for Alexa and Amazon Echo ML systems. Day to day you assign work, monitor queue adherence, volume and quality, hire and train associates, build weekly schedules across competing workflows, and track quality and utilisation metrics. You liaise with program management and global operations leads on risk mitigation and drive process improvement using Kaizen, Six Sigma or lean methods.

University of Cambridge · Cambridge · £33,662 – £46,970 pa

Lead a workstream within the IMPACT-OC European consortium, building a multi-agent AI system for ovarian cancer that spans imaging, genomics, histopathology and clinical records with privacy-preserving federated learning. The role is jointly based in the Department of Radiology and the Early Cancer Institute, combining multimodal AI pipelines, digital twin technology and clinician-facing deployment across eight partner institutions.

Anthropic · London · £265,000 – £375,000 pa

Paid, fixed-term research residency of six weeks to six months for people transitioning into empirical AI safety work, with a scoped project and direct mentorship from Anthropic researchers. Residents get access to Claude models and GPU compute and work on areas such as scalable oversight, interpretability, adversarial robustness, AI control, safeguards, and frontier red-teaming.

ECM Selection · London · £46,000 – £52,000 pa

Join a national security team building robust AI agents and realistic training environments to defend critical infrastructure from cyber threats. Day-to-day work spans realistic network simulation environments, novel agent architectures, and evaluation tasks, requiring strong Python, Linux and git skills plus a research mindset. Hybrid role with just one day per week in the central London office.

HAYS Specialist Recruitment · London · £70,000 – £90,000 pa

Designs and builds modern machine learning and AI services within a collaborative data team, developing and optimising data pipelines across a cloud analytics platform. Works with PySpark, Python, SQL, Databricks or Snowflake on AWS, plus Airflow, Terraform, Docker and Kubernetes, in agile squads supporting ML and GenAI infrastructure.