Artificial Intelligence Jobs

Wayve · London

Lead functional safety activities for an end-to-end autonomous driving system, building Item Definitions, running HARA/FMEA/FTA analyses, and shaping safety concepts and architectures across vehicle platforms and third-party systems. Define verification and validation, including vehicle-level testing, and construct structured safety cases with claims, arguments and evidence to support certification.

Wayve · London

Build and operate a globally distributed Data Transfer Hub moving petabytes of video, LiDAR and sensor data per day between Wayve and partners such as Uber, Stellantis and Nissan. Write pipeline logic in Python, manage infrastructure with Terraform, and use Flyte, Kafka and Azure for orchestration, event-driven lifecycle tracking and storage. The small, high-autonomy team owns production reliability, observability and cost efficiency, with an out-of-hours on-call rotation once the service is established.

University of Exeter · Exeter · £21,805 pa

Develops explainable, trustworthy machine-learning models for early dementia detection, integrating multimodal data such as neuroimaging, cognitive assessments, genetics and biomarkers. Uses latent knowledge-enhanced representations, vision-language agentic frameworks and uncertainty quantification, with clinician evaluation of bias and fairness. Validated through a longitudinal multimodal prediction and explanation system.

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.

Barclays · London

Owns the optimisation and strategy of transaction monitoring controls across Barclays UK and International, tuning surveillance systems and developing detection solutions. Involves data exploration, SQL/Scala/Spark/Python coding, and engaging technical and non-technical stakeholders on financial crime risk. Based in Canary Wharf or Glasgow.

NVIDIA · Reading

Serve as the first line of technical expertise between NVIDIA, Hyperscaler partners and end-customers, with a primary focus on the Google Cloud (GCP) partnership. Develop and demonstrate GenAI and accelerated computing solutions, optimise GPU training and inference pipelines, and engage developers, researchers and senior technical leaders.

Amazon · London

Lead end-to-end delivery of complex AI/ML engagements for enterprise customers, from strategic planning through pre-production deployment and optimisation. Architect solutions on AWS services with a focus on Generative AI using Amazon Bedrock and SageMaker, while mentoring junior consultants and supporting pre-sales scoping. Based in AWS UK offices when not at customer sites.

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.

NVIDIA · France

Serve as the first line of technical expertise between NVIDIA, hyperscaler partners and end-customers, with a primary focus on the Google Cloud (GCP) partnership. Day to day involves proof-of-concept demonstrations, optimising GPU-accelerated training and inference pipelines, and engaging developers, researchers and technical executives to evangelise accelerated computing and Generative AI.

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.

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.

Databricks · London

Drives large-scale enterprise data warehouse migrations onto the Databricks Intelligence Platform across EMEA, partnering with GTM leadership, product specialists and account teams to shape adoption strategy. Acts as the tier-3 escalation point for complex or stalled migrations, builds assessment tooling and programmatic migration assets, and mentors the regional Solutions Architect community. Also feeds field insights back to Product and Engineering and authors whitepapers and conference talks.

The Francis Crick Institute · London · £47,500 pa

Lead a computational project modelling how driver mutation clones interact with their microenvironment in chronic liver disease and liver cancer. Develop graph neural networks, transformers and generative AI on large-scale spatial transcriptomics, single-cell and imaging data, in a cross-institutional collaboration with the Wellcome Sanger Institute's Lotfollahi Lab.

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.