Artificial Intelligence Jobs

Faculty · London

Lead the design, build and deployment of production-grade machine learning systems for clients across pharma, healthcare and other sectors. Work spans architectural decisions, scalable infrastructure, MLOps standards and mentoring junior engineers, with a strong client-facing advisory element. Requires deep Python, TensorFlow or PyTorch, and cloud plus Docker/Kubernetes experience.

Faculty · Remote (UK)

Lead the design, build and deployment of production-grade ML systems for defence clients, covering architecture, scalable infrastructure and MLOps standards. Work cross-functionally with engineers, data scientists and commercial teams, acting as a technical advisor and mentoring junior engineers. Requires on-site work with customers 2-4 days per week and eligibility for UK Security Clearance.

Wayve · London

Develop next-generation generative world models and planners such as GAIA, simulating complex driving environments for faster training and scalable deployment. Work spans diffusion and transformer architectures, latent compression, context pruning and inference-latency optimisation, with closed-loop agent interaction and sim-to-real evaluation. The role combines ML research, multi-modal modelling and production deployment, including mentoring and publishing.

University of Exeter · Exeter · £21,805 pa

Develops a multiscale Scientific Machine Learning digital-twin framework to predict thermal trajectories, torque capability and efficiency in low-speed, high-torque electric propulsion under extreme duty cycles. Combines physics-informed hybrid architectures (DNNs, neural state-space models, Neural ODEs) with safety-constrained dynamometer experiments at the Centre for Future Clean Mobility, in collaboration with marine power-systems company Ecomar Innovations.

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.

eFinancialCareers · London

Lead the build-out of a hedge fund's machine learning function, defining research strategy and hiring a team of ML researchers and engineers. Directs work in deep learning, reinforcement learning, probabilistic and time-series modelling, and generative AI, partnering with quant and investment teams on alpha generation, forecasting, portfolio construction, risk and execution. Combines hands-on technical direction with strategic leadership.

University of Hertfordshire · Hatfield · £39,560 – £46,970 pa

Postdoctoral role delivering research on innovative AI/ML algorithms for predictive modelling and optimisation of agricultural applications from heterogeneous data, as part of an Innovate UK-funded collaborative project. Involves developing AI/ML software tools, data management and analysis, supporting the Principal Investigator on project milestones, and contributing to publications and reports.

UCL · London · £46,261 – £48,679 pa

Develop and evaluate novel AI algorithms to quantify brain iron load from standard-format MRI data, with a focus on quantitative susceptibility mapping (QSM). Based in UCL's Hawkes Institute, a multidisciplinary grouping at the intersection of engineering and health, within a top-ranked computer science department.

The University of Manchester · Manchester · £48,337 – £59,390 pa

Develops and applies machine-learning and AI methods to protein engineering and enzyme design, analysing large biological, chemical and experimental datasets and building predictive models and computational tools. Works within an interdisciplinary group spanning the Manchester Institute of Biotechnology and Department of Chemistry, providing ML and data-science expertise, training and support to postdocs and students, and contributing to publications and funding bids.

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.

Anthropic · London · £260,000 – £630,000 pa

Blends research and engineering to advance reinforcement learning for large language models, building agentic capabilities like computer use and autonomous code generation. Involves architecting distributed RL training infrastructure across GPU clusters, designing novel training environments and evaluations, and profiling and optimizing the stack. Works closely with alignment, red team, and production training groups.

Anthropic · London · £370,000 – £630,000 pa

Builds and improves the core RL training infrastructure researchers rely on, profiling, debugging and rearchitecting bottlenecks across the stack. Partners with researchers and adjacent engineering teams to ship tooling that speeds up training runs, owning reliability and performance end-to-end.

University of Cambridge · Cambridge · £63,606 – £67,468 pa

The role involves contributing to research and teaching in artificial intelligence and machine learning, with a focus on fundamental ML, novel models and architectures. The appointee will develop graduate content for the MPhil in Advanced Computer Science, contribute to undergraduate teaching, and build a research team supported by external funding.

Capital One · Mansfield

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.

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.