Artificial Intelligence Jobs

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.

Faculty · London

Builds client-facing products that visualise insights from data scientists, working in cross-functional delivery teams within the National Security and AI Safety unit. Owns frontend standards and reusable component libraries across the company, sets up deployment infrastructure, and mentors other engineers. Requires React, TypeScript, ES6, HTML/CSS3 and data visualisation such as d3, with cloud exposure to AWS, GCP or Azure.

Faculty · London

Deliver bespoke, production-grade machine learning systems for government and national security clients, spanning the full ML lifecycle from architecture to deployment. Work with Python, Scikit-learn, TensorFlow or PyTorch, plus cloud platforms and Docker/Kubernetes, while advising stakeholders and setting deployment standards.

Anonymous · Birmingham · £35,000 – £38,000 pa

Graduate role bridging business users and technical teams, investigating processes, analysing data and identifying where process change, automation or AI can improve efficiency. Involves process mapping, requirements gathering, system testing and supporting implementation of technology-led solutions, with mentoring and exposure to real transformation projects.

University of Exeter · Exeter · £21,805 pa

Investigates whether small language models running on local workstations or on-premises servers can serve as reliable agents for bounded business workflows. The student will distil agentic capability from large teacher models via harness optimisation and fine-tuning on execution traces, measuring reliability, cost, latency and data locality, and releasing open tooling for UK SMEs.

PhysicsX · London

Builds the simulation side of Large Physics Models, generating multi-fidelity CFD data to train large-scale ML models. Develops solvers and numerical methods in differentiable or GPU-native frameworks such as JAX or NVIDIA Warp, using commercial and open-source CFD tools for reference data. Works in a research team alongside ML researchers, shaping data generation strategy and fidelity tradeoffs.

Isomorphic Labs · London

Join the model performance and scaling team to implement and optimize LLM post-training methods on frontier models, collaborating with research teams to turn new methods into production-ready systems. The role focuses on distributed training and inference performance, low-precision methods, and frameworks like JAX or PyTorch, in a hybrid London setting.

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.

Anthropic · London · £225,000 – £255,000 pa

Partner-facing role embedding with nonprofits, research institutes and academic medical centres to apply Claude to clinical development for rare and neglected diseases. You'll help design and review trials, build drug-repurposing tools from literature, omics and patient data, and create reusable infrastructure like MCP servers and benchmarks.

OpenAI · London

Join the training team to push the frontier of LLM development for flagship models, enhancing intelligence, efficiency, and adding new capabilities. Work spans architecture design, long-context and efficient attention, optimization, and the science of scaling, with hands-on prototyping, debugging, and infrastructure contributions.

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.

University of Birmingham · Birmingham · £21,805 pa

Develops a physics-informed AI framework to design and optimise alternative cooling mechanisms and refrigeration cycles, integrating thermodynamic modelling, machine learning and multi-objective optimisation. Experimental work validates selected combinations, with scope to balance computational and lab effort. Based in the School of Chemical Engineering alongside sustainable cooling and energy storage research centres.

Helsing · Berlin, Germany

Integrates state-of-the-art AI and software into complex customer systems, working directly with avionics engineers and partners to understand unfamiliar data structures, APIs and network protocols, then building adapters to connect them to Helsing's cloud infrastructure. Owns delivery end-to-end, from formalising requirements and fixing bugs to shipping features and running technology demonstrations in simulations or on real systems.

Latent Labs · London

Customer-facing engineering role deploying frontier generative biology models into pharma and biotech environments, owning the full lifecycle from technical scoping to production delivery. Involves building API integrations, data pipelines and model-serving infrastructure on AWS with Docker and Kubernetes, plus on-site work with international partners.

eFinancialCareers · London

Develops predictive machine learning models for fixed income and credit markets, covering issuer credit deterioration, transaction costs, liquidity forecasting and relative-value opportunities. Also builds LLM-powered document intelligence systems to extract structured data from filings, transcripts and prospectuses, with a strong emphasis on out-of-sample validation, explainability and production data pipelines.