Artificial Intelligence Jobs

Faculty · London

Serve as a high-level technical authority steering the most complex AI projects, architecting scalable large-scale systems and setting technical direction for flagship initiatives. Provide authoritative advice across business units, influence company-wide technical strategy, and act as a respected expert for internal teams and external customers in the financial services space.

Faculty · London

Lead the design, build and deployment of production-grade machine learning systems for clients across pharma, healthcare and other sectors. Work spans architectural decisions, scalable infrastructure, MLOps standards and mentoring junior engineers, with a strong client-facing advisory element. Requires deep Python, TensorFlow or PyTorch, and cloud plus Docker/Kubernetes experience.

Wayve · London

Develop next-generation generative world models and planners such as GAIA, simulating complex driving environments for faster training and scalable deployment. Work spans diffusion and transformer architectures, latent compression, context pruning and inference-latency optimisation, with closed-loop agent interaction and sim-to-real evaluation. The role combines ML research, multi-modal modelling and production deployment, including mentoring and publishing.

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.

Thought Machine · Lisbon, Portugal

Builds end-to-end features across web applications and backend services, owning requirements from engineering design through task breakdown, implementation and production debugging. Works with React, TypeScript and REST APIs in a cross-functional team of backend, front-end and full-stack engineers, with automated testing integrated throughout the development lifecycle.

Thought Machine · London

Owns complex, ambiguous technical challenges end-to-end, shaping long-term architecture and engineering standards across cloud-native banking platforms. Acts as a link between senior leadership and engineering teams, driving systemic change, mentoring senior engineers, and improving production operations. Uses Go/Python and AI tooling to scale developer velocity.

Amazon · London

Lead teams of technicians running AWS data centre operations, owning the full infrastructure lifecycle from rack installation and break-fix maintenance to decommissioning. The role spans building new sites, vendor management, health and safety compliance, and adopting high-density GPU, AI accelerator and liquid-cooling technologies, with a focus on automation and operational metrics.

Latent Labs · London

Work at the interface between frontier generative models and pharmaceutical/biotech customers, deploying, adapting and fine-tuning models in customer environments. Build production-grade API integrations, model-serving infrastructure and ML data pipelines, while acting as technical point of contact for partners. Combines deep ML research with customer-facing delivery in an interdisciplinary team.

Ncounter · Reading · £120,000 – £140,000 pa

Hands-on engineering leadership role in a technology consultancy serving National Security & Defence, blending people management with technical ownership. You'll lead a multidisciplinary software, platform and DevOps team, define architecture and standards across cloud-native, AI/ML and MLOps platforms, and oversee production delivery into customer environments. Distinct for requiring SC or DV clearance and defence experience while remaining close to the technology.

Relation Therapeutics · London

Lead the platform engineering team owning hybrid on-prem and cloud compute, Kubernetes clusters, MLOps infrastructure and scientific compute environments for machine learning and drug discovery. Set architectural strategy, mature CI/CD and observability, and own platform security and data governance for sensitive patient-derived data, reporting to the VP of Engineering.

Ncounter · Reading · £120,000 – £140,000 pa

Hands-on engineering leadership role overseeing a multidisciplinary team of software, platform and DevOps engineers. You'll own technical architecture and standards across cloud-native applications, AI/ML platforms and MLOps, while remaining close to delivery and shaping longer-term technical strategy for National Security and Defence customers.

Anthropic · London · £195,000 – £245,000 pa

This role involves conducting empirical economic research to understand AI's impact on labor markets, productivity, and economic transformation across a specific region. The economist will develop and expand the Anthropic Economic Index using novel measurement systems like Clio, applying advanced econometric and machine learning methods. They will collaborate with governments, academia, and policy institutions to translate research into actionable insights and influence both public policy and internal business decisions.

eFinancialCareers · London

Leads the design, development and operation of high-rigor analytical and machine-learning systems across a complex, regulated financial-services estate, defining the AI/ML roadmap while remaining hands-on. Owns the full model lifecycle from feature engineering and back-testing to deployment, monitoring and incident response, with models expected to be explainable and production-grade. Works closely with engineering, data platform and product teams, mentoring other data scientists with limited line management.

eFinancialCareers · Belfast

Hands-on player-manager role leading a growing Data & Analytics function, combining Power BI development, SQL analysis and AI exploration with stakeholder management and delivery leadership. You will build dashboards and semantic models, manage the Power BI environment and backlog, prototype HTML-based analytical applications, and apply generative AI and Copilot to improve reporting while coaching analysts and engineers.

Relation Therapeutics · London

Design and implement generative models that learn intervention effects from single-cell perturbation and multiomic data, focusing on counterfactual prediction, generalisation and experimental design. Work in interdisciplinary teams with experimental biologists to validate computational hypotheses and guide the highest-signal next experiments, using modern ML tooling including agentic workflows.