Artificial Intelligence Jobs

Faculty · Remote (UK)

Lead the technical direction and delivery of complex, high-risk AI projects for defence clients, balancing deep ML engineering with team leadership. You'll design scalable ML systems, set architecture, build shared libraries, mentor engineers, and work on-site with customers 2-4 days a week, with the rest remote or from the London office.

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.

Wayve · London

Owns the technical vision and architecture for a platform that lets model engineers deploy, run, evaluate and improve ML models over petabytes of driving data and large GPU fleets. Combines hands-on backend engineering in Python with cross-team technical leadership, mentoring senior engineers and leading a small team of 2-3.

Harnham - Data and Analytics Recruitment · London · £100,000 – £140,000 pa

Build and lead multimodal AI applications spanning text, audio and video, including AI-generated avatars and automated content summarisation, within a growing AI team in a mature data function. The role involves translating business needs into scalable, production-deployed AI products and collaborating with a multidisciplinary team, with technical leadership duties at Lead level.

Data Idols · London · £105,000 – £120,000 pa

Hands-on technical leadership role driving the design, development and deployment of AI, Machine Learning and Generative AI solutions, including LLMs and agentic AI. Partners with business and technology stakeholders to identify high-value use cases, prototype rapidly and take solutions through to production, while shaping the AI technical roadmap and engineering best practices.

Ocado · Sofia, Bulgaria

Maintains and improves a live customer-facing slot-availability application while writing Terraform/OpenTofu infrastructure as code for cloud environments. Extends backend services, APIs and data pipelines, and modernises the platform by tuning Airflow/Composer and reducing technical debt. Works in a small distributed team with monitoring, alerting and incident response duties.

eFinancialCareers · London

You will partner with portfolio managers, analysts and researchers to understand investment workflows, then design, build and deploy AI-powered applications and data tools for front-office teams. The role sits in a central Data & AI team, integrating large-scale data, machine learning models and modern software engineering practices in a fast-paced hedge fund environment.

Entrust · Paris, France

Owns planning, coordination and execution of testing across a cross-functional identity verification product team, covering web, mobile, backend services and ML-powered products. Builds maintainable automated test frameworks and suites, mentors colleagues, and contributes to org-wide quality and tooling initiatives. Combines automation with exploratory testing in a team of nine embedded test engineers.

Entrust · London

Owns test planning, coordination and execution within a cross-functional identity verification product team, covering web, mobile, backend and ML-powered journeys. Builds maintainable automated test frameworks, combines automation with exploratory testing, and mentors colleagues while improving CI/CD pipelines and release feedback loops.

Tenth Revolution Group · London · £75,000 – £105,000 pa

Builds and deploys production LLM and Generative AI applications for enterprise clients, including RAG solutions, scalable data pipelines and AI-powered services. Works in a collaborative consultancy team of engineers and architects, applying software engineering best practices to take AI from proof of concept into production, with monitoring and optimisation of live systems.

Harnham - Data and Analytics Recruitment · London · £80,000 – £85,000 pa

Design, build and deploy scalable AI and machine learning solutions from concept to production, including Generative AI applications using LLMs and orchestration frameworks. Write production-grade Python, apply MLOps practices such as CI/CD, containerisation and monitoring, and build data pipelines for training, fine-tuning and inference. Work hybrid in London alongside data scientists, engineers and business stakeholders on large-scale datasets.

Relation Therapeutics · London

Join the Platform Team to design and scale Kubernetes-based hybrid compute clusters across private and public clouds, building core platform services and APIs. You will own CI/CD pipelines, monitoring, backup and disaster recovery, and work closely with Machine Learning and Data Science teams to support their computational needs.

eFinancialCareers · London

Architects, deploys and supports machine learning and GenAI infrastructure on AWS, building CI/CD pipelines and turning data science models into production systems. Works within an AI Enablement team using Terraform, Jenkins, Kubernetes and SageMaker, with a focus on auditability, versioning and data security while liaising with clients on requirements.

Anthropic · London · £325,000 – £390,000 pa

Lead and scope multi-month infrastructure projects, making architectural decisions for large-scale distributed systems that train and serve AI models. Work spans Kubernetes clusters, data pipelines, databases and observability tooling, partnering with research and product teams while mentoring engineers and shaping incident response and on-call practices.

AI Security Institute · London

Senior individual contributor building and owning shared platform, tooling and infrastructure for a research team, including LLM-based agent systems, evaluation frameworks and supporting infrastructure. Works closely with interdisciplinary researchers to translate varied needs into maintainable Python systems, with strong engineering discipline around testing, documentation and observability. Also contributes to architectural decisions, engineering standards and mentoring through code review and knowledge sharing.