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.

Square One Resources · London · £600 – £700 pd

Builds production-grade Python services for Generative AI and complex RAG solutions, covering LLM workflow orchestration, retrieval, evidence processing, response generation and validation. Involves asynchronous services, vector/lexical/hybrid retrieval, Pydantic and LangGraph-style orchestration, plus automated testing and observability. Requires delivering GenAI and RAG beyond proof of concept.

Matchtech · Cambridgeshire · £450 – £650 pd

Contract Python developer role focused on building and maintaining software for integration with a defence cloud environment. Day-to-day work spans data and AI, automation and tooling, and DevOps, using Red Hat OpenShift, Quay, HashiCorp Vault, Tekton Pipelines, GitHub, ArgoCD and SonarQube within agile teams. Requires UK Eyes Only clearance eligibility and is based on-site/hybrid in Cambridgeshire.

Advancing People · Brussels, Belgium

Builds and maintains Python-based Intelligent Document Processing pipelines, focusing on AI-driven document understanding such as data extraction and classification. Works in a product team alongside AI, front-end and infrastructure engineers, using LLMs, Flask/Django/FastAPI and cloud infrastructure. Requires two days per week in the Brussels office.

Experis · London · £600 – £644 pd

Builds production-grade GenAI and Agentic AI products within a product squad, using LLMs, RAG and agentic workflows. Requires strong Python engineering plus LangGraph, vector search, evaluation and Azure AI services to deliver secure, maintainable AI applications.

NXA Talent LTD · London · £500 pd

Design and build agentic AI systems with multi-step reasoning, multi-agent orchestration and scalable AI microservices in Python and Azure OpenAI. Develop RAG architectures, vector search and orchestration workflows using Semantic Kernel and LangGraph, integrating enterprise systems via MCP. The role also covers AI governance, safety and deploying LLM services into production within a large retail environment.

Quantum Group · London · £42,000 – £45,000 pa

Analyse aged-receivables, debtor and payment data to identify credit and counterparty risk, estimate expected losses, and assess liquidity and cash-flow exposures. Build Python statistical models for default prediction, run stress tests, and develop Power BI dashboards tracking debtor days and collection rates. Maintain the risk register, prepare monthly leadership reports, and support audit and compliance work.

Michael Page · Leeds · £40,000 – £48,000 pa

Analyse large datasets to uncover trends and build predictive models and algorithms that support strategic decisions in a financial services setting. Work within a collaborative analytics team, presenting findings to non-technical stakeholders and helping maintain data pipelines and infrastructure. Requires Python, R or SQL plus statistical and machine learning techniques, with GIS tooling also desirable.

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.

Flarebright · Bicester · £39,000 – £49,000 pa

Contributes across the full development lifecycle, from concept and algorithm design to system integration, testing and troubleshooting of safety-critical navigation and autonomy software in C++. Works with a multidisciplinary team on real-time embedded systems, hardware/software-in-the-loop testing and flight test activities, producing design documentation and test reports.

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.

Anthropic · London

Conduct experimental research on AI safety, focusing on alignment and robustness of advanced systems. Develop and test techniques like AI debate and jailbreak evaluation, contributing to publications and safety policy. Work in a collaborative, interdisciplinary team using machine learning and systems engineering.

Wayve · London

Builds ground-truth datasets and computer vision classifiers that describe complex driving scenes across Wayve's data corpus, drawing on the World Foundation Model to surface rare scenarios and performance gaps. Day to day spans defining annotation tasks and quality criteria, curating datasets, training and evaluating models in PyTorch, and integrating classifiers into enrichment infrastructure for corpus-wide inference.

Wayve · London

Lead a London-based team building the on-vehicle experiment platform that lets researchers deploy driving models to vehicles, run experiments and collect training data. You own people, roadmap and delivery, plus partner and OEM relationships, while staying close to embedded Linux systems code in C++ or Python.

Cranfield University · Bedford · £38,655 – £46,492 pa

Integrates four strands of AI research into a single flight-deck assistant and validates it with airline pilots in Cranfield's Future Systems Simulator. Builds the software platform and automated test framework for real-time operation, creates flight scenarios, runs simulator trials and publishes findings within an EU Horizon Europe project.

ElevenLabs · United Kingdom

Builds and scales data pipelines from ingestion to delivery, implementing dbt best practices, data standards and quality controls. Develops self-service tooling and documentation so teams like Engineering, RevOps and Growth can access data independently, and creates AI agents to answer data questions. Works remotely within a lean, high-velocity data team.