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.

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.

Amazon · London

Join the Audible Research team to advance computer-generated speech, developing novel deep learning algorithms and modelling techniques for spoken language generation. You will design, evaluate and deploy data-driven models using large-scale computing resources, while leading and mentoring junior engineers and scientists.

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.

Reperio Human Capital · Dublin, Ireland · £388 – £474 pd

Hands-on engineering role owning AI/ML initiatives end-to-end, from solution design and experimentation through deployment, monitoring and optimisation. Involves building production ML and GenAI solutions including RAG architectures, working with Snowflake and cloud data platforms, and developing Python and R software with strong MLOps, CI/CD and DevSecOps practices. Collaborates with data, product and business teams to turn ambiguous problems into scalable, secure solutions.

Faculty · London

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

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.

Faculty · Remote (UK)

Deliver bespoke, production-grade machine learning systems for defence clients, covering the full ML lifecycle from architecture and scoping to deployment. Work with Python, Scikit-learn, TensorFlow or PyTorch, plus cloud platforms and Docker/Kubernetes, splitting time between client sites and remote work.

Sanderson · London · £550 – £700 pd

Builds, deploys and maintains machine learning models and end-to-end ML pipelines in a modern cloud environment, writing production-quality Python and SQL. Works with data scientists, analysts and engineers to take AI products from proof of concept to production, including NLP and large language model work, plus monitoring and documentation.

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.

Wayve · London

Post-train, distill and evaluate GAIA-family large video diffusion world models for synthetic driving data, covering embodiment and pose transfer. Own large-scale GPU generation pipelines and land synthetic data into the driving-model training stack, working between ML research and platform engineering.

Wayve · London

Lead a small team iterating on Wayve's end-to-end L2 driving model, balancing hands-on Python coding and experiments with directing priorities. You'll root-cause on-road issues and fix them through data recipes, model architecture, evaluation and release readiness, working across teams on model and vehicle interface problems.

Aioi Nissay Dowa Europe · United Kingdom · £81,322 – £112,488 pa

Dual role combining line management of a growing ML engineering team with hands-on technical delivery across multiple client projects. You'll shape ML engineering practice, lead multidisciplinary teams, oversee solution design and quality assurance, and support pre-sales and use case discovery alongside commercial teams.

DCV Technologies · Manchester · £550 – £600 pd

Contract role building and deploying production AI/ML systems, with hands-on work in Python, PyTorch and Google Cloud Platform. The engineer develops Generative AI solutions using transformer architectures, RAG and agent frameworks like ReAct, then packages and serves models via Docker, KServe and Vertex AI endpoints. Responsibilities also cover MLOps practices such as CI/CD pipelines, model registries, monitoring, drift detection and GPU cost optimisation.

WeDoTech · London · £120,000 – £160,000 pa

Hands-on technical leadership role building and scaling enterprise Generative AI, LLM and agentic AI systems across multiple engineering teams. Involves designing production-grade RAG and multi-agent solutions, shaping reusable AI frameworks and standards, and ensuring reliability and governance in a regulated financial services environment.

Ocado · Kraków, Poland

Senior ML engineer role in a cross-craft data science team building prediction, ranking and personalisation systems for an e-commerce platform. Owns the full ML lifecycle on production systems, from experimentation and training through serving, monitoring and MLOps, while coaching others and shaping reusable platform building blocks.