Artificial Intelligence Jobs

University of Exeter · Exeter · £21,805 pa

Develops and evaluates AI, machine learning and deep learning methods for grading retinal fundus images to detect diabetic retinopathy, glaucoma, cataract and AMD. Works with large datasets including EyePACS, UK Biobank and NHS sources, comparing algorithm accuracy against NHS clinicians and optimising explainable models for clinical trust.

University of Exeter · Exeter · £21,805 pa

An interdisciplinary PhD co-designing miniaturised, low-power sensing hardware with AI for field-based wildlife monitoring, including individual recognition and automated behaviour quantification. Systems are benchmarked in controlled conditions then validated on wild jackdaws and West African field sites, spanning behavioural ecology, electronic engineering and data science.

Relation Therapeutics · London

You will partner with Programme and Project Leaders to shape delivery plans and drive an osteoporosis programme through target ID, hit-to-lead, lead optimisation and candidate selection. The role involves orchestrating matrixed wet lab, ML, data science and engineering teams, managing budgets, risks and governance, and coordinating third-party partners such as CROs.

Relation Therapeutics · London

Lead the platform engineering team owning hybrid on-prem and cloud compute, Kubernetes clusters, MLOps infrastructure and scientific compute environments for machine learning and drug discovery. Set architectural strategy, mature CI/CD and observability, and own platform security and data governance for sensitive patient-derived data, reporting to the VP of Engineering.

NVIDIA · Bristol

Research and develop techniques to GPU-accelerate deep learning, machine learning and other AI workloads, working with technical experts from industry and academia to analyse and optimise complex AI and HPC algorithms on modern CPU and GPU architectures. The intern also publishes optimisation techniques via developer blogs or conferences and helps influence next-generation hardware, software and programming models.

NVIDIA · Zürich, Switzerland

Research and develop techniques to GPU-accelerate deep learning, machine learning and other AI workloads, working with technical experts to analyse and optimise complex AI and HPC algorithms on modern CPU and GPU architectures. The role also involves publishing optimisation techniques via developer blogs or conferences and influencing next-generation hardware and software design.

Faculty · London

Owns and grows key Life Sciences accounts, acting as a strategic partner to pharma, academic and MedTech clients. Leads a cross-functional team of delivery and engagement specialists, driving commercial negotiations, sales planning and forecasting while translating complex AI concepts into client use cases.

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.

University of Surrey · Guildford · £21,805 pa

Develops next-generation federated machine unlearning algorithms that deliver verifiable, robust erasure without harming model performance or participant privacy. Research spans certified unlearning with formal guarantees, robustness to adversarial relearning, federated-specific benchmarks, and scalable unlearning for foundation models, supervised by Dr Pedro Porto Buarque de Gusmao and Dr Frank Guerin.

University of Surrey · Guildford · £21,805 pa

Develops a computational framework combining computer vision, graphics and machine learning to speed up and improve cinematic camera lens design and simulation. The work covers forward simulation of candidate lens configurations and inverse design of lens architectures against imaging or perceptual objectives, using differentiable rendering and data-driven models. Based at the Vision, Speech and Signal Processing group under Dr Marco Volino and Dr Jean-Yves Guillemaut, with close industry collaboration.

Scale AI · London

New grad engineers own customer-facing work from day one, shipping products, speaking directly with customers and iterating quickly. The Global Public Sector team builds custom AI applications, training data pipelines for national LLMs, evaluation infrastructure, agentic AI tooling and fraud-detection systems, working in Python, TypeScript, React and MongoDB.

Scale AI · London

Interns own real, shipped work on the same roadmaps as full-time engineers, building agentic AI applications, evaluation infrastructure, data pipelines and fraud-detection systems for Scale's Global Public Sector team. Work spans Python, TypeScript, React and MongoDB, with mentorship and a strong ownership culture.

Isomorphic Labs · London

Lead all externalised drug discovery and preclinical lab operations, building and scaling a global CRO infrastructure for an AI-first drug design platform. Oversee experimental throughput, data QC and turnaround times, embed data-generation-by-design standards with Data Engineering, and manage vendor governance, budgets and a team of CRO Scientific Leads, Operations Managers and Compound Managers.

Isomorphic Labs · Cambridge, United States

Lead and execute the translational medicine strategy across oncology programs, ensuring clinical biomarker assay readiness and data delivery to inform mechanism of action, resistance and future indications. Serve as a core program team member and cancer biology expert, collaborating with AI and computational biology teams to build innovative biomarker analysis tools and advance companion diagnostics.

University of Oxford · Oxford · £21,805 pa

Investigates how the rapid growth of AI can be supported by more sustainable, circular hardware and infrastructure, linking computational performance to the physical materials and equipment required. Develops scenarios for UK AI and data centre growth, mapping hardware requirements to critical raw materials and modelling how lifetime extension, reuse, repair and remanufacture could cut environmental impacts. Based in the Circular Economy and Sustainability Lab, contributing to the Circular Electricals and Electronics Project.