Artificial Intelligence Jobs in Leeds

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.

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.

Carrington Recruitment Solutions · Leeds · £70,000 – £75,000 pa

Hands-on full stack engineering role guiding a small development team while collaborating with Product and Architecture. You'll build and shape delivery standards across C#, .NET, Python, Azure PaaS and React, with an AI-native edge using GenAI tooling and taking experiments through to production.

Anthropic · London · £265,000 – £375,000 pa

Paid, fixed-term research residency of six weeks to six months for people transitioning into empirical AI safety work, with a scoped project and direct mentorship from Anthropic researchers. Residents get access to Claude models and GPU compute and work on areas such as scalable oversight, interpretability, adversarial robustness, AI control, safeguards, and frontier red-teaming.

Databricks · London

Customer-facing, billable engineering role owning architecture and design decisions while building production-grade data and AI systems on the Databricks platform. Involves embedding with client teams, integrating with their systems, and delivering end-to-end pipelines, ML/AI models and user-facing applications, with around 20% travel to customer sites.

Wayve · London

Leads complex, multi-team programmes across Level 2 and Level 4 autonomous driving products, translating product milestones into integrated cross-team schedules and delivery plans. Reviews technical progress, backlog health and system-level evidence to assess milestone readiness, managing dependencies and critical-path activities across engineering, product, safety and validation. Improves lifecycle-planning practices and tooling to surface risk earlier and deliver more predictably.

OpenAI · London

Senior technical owner for a portfolio of public sector customers, shaping AI strategy from pre-sales discovery through production adoption. Owns the technical account plan across ChatGPT Enterprise, the OpenAI API, Codex and agentic solutions, designing architectures spanning models, data, integration, identity, security and governance while coordinating deployment, enablement and partner specialists.

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.

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.

Faculty · London

Builds and deploys production-grade machine learning systems for national security and AI safety clients, including LLM applications, multi-agent tooling and evaluation of frontier models. Involves technical scoping, architectural decisions, and advising stakeholders, with reusable infrastructure work alongside engineers and data scientists.

NVIDIA · United Kingdom

Lead NVIDIA's developer strategy with a major cloud service provider, driving GPU acceleration adoption across AI and generative AI workloads. The role blends developer advocacy, product management and business development, building engineering partnerships and hosting summits and meetups. High visibility with senior leadership in a strategic deep learning and HPC area.

Isomorphic Labs · Cambridge, United States

Designs and leads in vitro and cellular pharmacology strategies for small-molecule drug discovery programmes, defining screening cascades and overseeing biophysical, biochemical and cell-based assays. Works closely with AI/ML, medicinal chemistry, structural biology and in vivo teams, and manages external CRO activities to link computational predictions with laboratory validation. Some roles include line management of 2-3 scientists.

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.

Faculty · London

Builds and deploys production-grade ML software, tools and infrastructure, creating reusable solutions that accelerate ML delivery and capability testing of frontier AI models. Leads technical scoping and architectural decisions, advises clients and partners, and works with frontier labs on AI safety red teaming and evaluation.

Faculty · London

Oversees a portfolio of Applied AI projects as the senior point of contact for clients and internal teams, managing delivery quality, commercial margins and scope. Combines strategic consulting with business development, writing proposals and growing accounts, while mentoring cross-functional teams using Agile, Scrum or Kanban. Based in the Professional and Financial Services unit serving highly regulated industries.

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.