Artificial Intelligence Jobs

Faculty · London

You will own and evolve the internal delivery platform that supports over 100 data scientists and ML engineers, building MLOps, data science and deployment tooling. Day to day involves infrastructure-as-code, DevSecOps, containerised microservices and integrating core services across AWS, Azure and GCP. The role sits in a small, fast-moving team focused on removing technical friction for customer-facing delivery teams.

PhysicsX · New York, United States · US$150,000 – US$250,000 pa

Builds and deploys customer-facing applications on top of physics AI models, working directly with clients, data scientists and ML engineers. Involves full-stack work: FastAPI REST APIs and Python microservices, plus cloud deployment with Helm, Kubernetes, Terraform and AWS/Azure. Expect on-site travel to customer sites for 3-4 weeks per quarter.

PhysicsX · Singapore

Lead technical delivery of physics-informed AI, architecting deep learning models and optimisation methods to predict and control physical systems. Own data pipelines and pre-processing best practices while mentoring a team and collaborating with simulation engineers and customers. Involves frequent on-site customer travel across multiple regions.

Faculty · London

Scoping, building and delivering bespoke AI solutions for pharmaceutical and life sciences clients, managing individual work streams and translating operational requirements into user stories for engineering teams. Involves open-source analysis, workflow design and close collaboration with data science and ML experts, with a focus on high-stakes, user-centric decision-making.

Isomorphic Labs · London

Builds greenfield machine learning models and algorithms for drug discovery, designing new architectures, running experiments, and scaling training and inference frameworks. Works in an interdisciplinary team of ML scientists and domain experts, with opportunities to lead projects and mentor others depending on experience.

Cranfield University · Cranfield · £21,805 pa

A PhD studentship researching AI-on-RAN, optimising distributed and mobile inference of large language models by adapting token, memory and bandwidth use in real time. The work spans AI and telecoms, with cross-university FTH training and exposure to defence, government and infrastructure stakeholders, aiming to shape 6G network design.

University of Sheffield · Sheffield · £39,560 – £43,099 pa

Postdoctoral role applying explainable NLP and machine learning to analyse online disinformation narratives, integrate findings into a user-facing verification toolkit, and evaluate commercial chatbots and AI-generated search overviews. The researcher joins the European-funded ANTIGONE project, collaborating with multidisciplinary partners and leading publication of results in high-impact journals and conferences.

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 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.

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.

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.

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.

Isomorphic Labs · London

Lead the hardening and scaling of an inference platform serving fleets of cutting-edge ML models for scientific applications. Set strategy and roadmaps, architect next-generation services to solve scaling limits, and partner with research, product and operations teams to align infrastructure with biotech R&D cycles.

Back TO Work · Gateshead · £25,900 pa

Join an educational software support company to help build an AI Agent, working across data preprocessing, exploratory analysis, model fine-tuning and implementation of machine learning algorithms. Collaborate with cross-functional teams to define requirements and deliver scalable solutions while keeping up with the latest AI advancements. Aimed at early-career candidates with no prior experience required.