Artificial Intelligence Jobs

Wayve · London

Develops and maintains Wayve's Core Simulation system in modern C++ and Python, integrating driving-stack components, simulated robot systems and vehicle-platform capabilities. Initially focused on high-scale open-loop evaluation, the role involves debugging on-road versus simulated behaviour, improving reproducibility, observability and automated testing, and profiling simulator performance across a shared codebase.

Wayve · London

Lead a London-based team building the on-vehicle experiment platform that lets researchers deploy driving models to vehicles, run experiments and collect training data. You own people, roadmap and delivery, plus partner and OEM relationships, while staying close to embedded Linux systems code in C++ or Python.

University of Oxford · Oxford · £39,424 – £47,779 pa

Develops novel statistical and machine learning methods for large-scale genomic, phenotypic and health data, covering areas such as genomic language models, multimodal and federated learning, and multi-ancestry methods. Builds scalable, reproducible research software applied to biobank-scale datasets, evaluates statistical and predictive performance, publishes findings and guides junior researchers in the Palamara Group.

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 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.

Reed · Cambridge

Lead statistical and bioinformatics analysis projects, developing computational algorithms and applying machine learning to functional genomics research. Work with NGS, OMICS and high-throughput datasets alongside laboratory scientists, using Python, R or Julia and libraries such as TensorFlow and PyTorch. The role also involves mentoring and cross-functional collaboration in a multidisciplinary research team.

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.

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.

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.

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.

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.

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.

University of Exeter · Penryn · £21,805 pa

Develops physics-aware spatio-temporal graph neural networks for 0–6-hour visibility forecasting, focusing on low-visibility events in southeast England. The work spans six packages, from benchmarking NWP and ML baselines to linking learned representations with atmospheric physics, testing robustness to degraded observations, and operational evaluation with Met Office scientists.

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.