Artificial Intelligence Jobs

Hadean · London

Lead a new AI-powered defence product team, line-managing AI/ML, simulation, infrastructure and web engineers while staying hands-on in TypeScript, React and Node. You own delivery end-to-end, hiring and people development, partnering with Product and technical leads, with hybrid working one day a week in Shoreditch.

Experis · London · £70,000 – £110,000 pa

Hands-on leadership role taking AI solutions from proof of concept to secure, production-grade deployments in regulated Security & Justice environments. Involves designing end-to-end AI architectures, leading multidisciplinary teams, shaping technical roadmaps and ensuring governance and security compliance across LLM, RAG and MLOps workstreams.

ECM Selection · Cambridge · £40,000 – £70,000 pa

This role involves developing end-to-end machine learning systems integrated with advanced electronics for defence and security applications. You'll work across diverse domains such as computer vision and generative models, building functional prototypes and demonstrators. The role emphasizes innovation, rapid iteration across projects, and close collaboration in a technically driven, low-management environment.

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.

Faculty · London

Lead the technical strategy, architecture and deployment of secure AI systems across high-stakes domains, bridging research and production impact. The role involves capability testing for Frontier AI models, multi-agent systems, scalable cloud infrastructure and safety-first frameworks, while advising senior clients and mentoring engineering talent.

Faculty · London

Drives technical strategy, architecture and deployment of secure AI systems across high-stakes domains, bridging AI research and production. Leads capability testing for Frontier AI models, builds scalable ML infrastructure and multi-agent tooling, and advises senior client stakeholders while mentoring engineers.

Luminance · Cambridge

Join a small, dynamic R&D team prototyping and implementing new approaches to AI problems, evaluating output quality, efficiency and feasibility against other techniques in a data-driven way. Work spans data science on large datasets, modelling and evaluation, using Python ML frameworks such as PyTorch, TensorFlow and Scikit-Learn. Open to graduates as well as senior candidates with published work in NLP, Computer Vision or Deep Learning.

Wayve · London

Builds reusable Python libraries and platform tooling for multimodal data loading, distributed training, inference, checkpointing and observability, supporting ML teams running models across thousands of GPUs. Partners closely with researchers to turn complex workflows into stable, scalable software, leading projects from discovery to delivery. A software and platform engineering role rather than ML modelling.

MFK Recruitment · Brentford · £70,000 – £95,000 pa

Design and deploy production-grade computer vision systems using deep learning techniques such as CNNs and Vision Transformers, translating research into robust AI solutions for defence and security applications. Work across the full development lifecycle, from model design and training to deployment on cloud and edge platforms. Collaborate with researchers, engineers, and customers in a technically challenging environment focused on real-world autonomy and perception systems.

Causaly · London

Design and ship ML/AI solutions end-to-end, from data exploration to deployment and monitoring, choosing between classical ML, NLP, LLM and agentic approaches. Work closely with product, design and engineering on user-facing AI features, champion model and data quality, and mentor junior engineers in a biomedical knowledge platform team.

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.

Capital One · Lincoln

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. The role involves setting technical direction, mentoring junior team members, and driving prototypes through to production in collaboration with business stakeholders.

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.

Parkside · London · £100,000 – £150,000 pa

Lead the development of AI features in a legal tech SaaS platform, building ML models for document parsing, search, classification and summarisation. Integrate LLMs with guardrails, evaluation and monitoring, and optimise model serving on AWS. Work hands-on in Scrum squads alongside engineering, product and QA.

Entrust · London

Builds and operates production ML systems for document classification and extraction, using LLMs/VLMs and traditional ML to process government identity documents at scale. Owns features from RFC through deployment, optimising GPU inference and training/evaluation pipelines, and mentors engineers within a squad-based team.

Entrust · Lisbon, Portugal

Builds and operates production ML systems for document classification and extraction, using VLM/LLMs and traditional ML to power identity verification for millions of users. Leads technical design from RFC to deployment, optimises GPU inference, and designs training, evaluation and labelling pipelines. Works in a squad-based team alongside Applied Science, Product and Data Science, mentoring engineers and driving reliability and scalability.