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.

University of Southampton · Southampton · £41,064 – £45,064 pa

Embed physics-informed generative AI tools into a marine vessel concept, generation and evaluation platform as part of a Knowledge Transfer Partnership between Compute Maritime Ltd and the University of Southampton. Develop and validate fast physics-informed models for ship resistance, propulsion and energy efficiency using CFD and benchmark data, and integrate multidisciplinary optimisation methods into the NeuralShipper platform.

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.

University of Essex · Milton Keynes · £41,950 pa

Develops novel computer vision techniques to capture and analyse live-broadcasted eSports events, identifying in-game events and building low-latency AI calculations for in-play betting markets. Works with Python, TensorFlow or PyTorch alongside Java and .NET colleagues, using historical game data and video feeds to detect irregular play patterns. A KTP partnership between the University of Essex and Sports Information Services Ltd.

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.

Spencer Rose · Bristol · £450 – £480 pd

Designs, builds and deploys end-to-end AI/ML solutions for a banking client's Coach AI programme, including LLM-powered assistants, copilots and multi-agent agentic systems. Involves production deployment, MLOps pipelines, NLP, computer vision and voice AI, plus AI guardrails, responsible-AI governance and mentoring a team as senior lead.

C4S Search Ltd · London · £600 – £650 pd

Designs, builds and deploys machine learning models into production, with a focus on recommendation systems such as personalised product recommendations, ranking and search optimisation. Works with data scientists, engineers and product stakeholders, maintaining MLOps pipelines for CI/CD, model versioning and monitoring on Azure, and retraining models to sustain accuracy on large-scale datasets.

WeDoTech · London · £800 – £1,000 pd

Senior hands-on staff engineer driving adoption of Agentic AI and production ML across multiple engineering teams. Defines reusable architectures and patterns, builds production RAG and LangGraph/LangChain systems, and improves AI evaluation, observability, MLOps and model-risk controls in a regulated environment.

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.

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.