Artificial Intelligence Jobs

Faculty · Remote (UK)

Lead backend and edge/IoT engineering for high-stakes Defence projects, bridging proof-of-concept work and robust production systems. You will mentor a squad of engineers, design complex components, and build CI/CD and containerisation pipelines with Docker and Kubernetes while shipping Python and compiled-language code alongside ML engineers and data scientists.

Faculty · London

Builds client-facing products that visualise insights from data scientists, working in cross-functional delivery teams within the National Security and AI Safety unit. Owns frontend standards and reusable component libraries across the company, sets up deployment infrastructure, and mentors other engineers. Requires React, TypeScript, ES6, HTML/CSS3 and data visualisation such as d3, with cloud exposure to AWS, GCP or Azure.

Carrington Recruitment Solutions · Manchester · £80,000 – £90,000 pa

Hands-on full stack lead role guiding a small development team across a portfolio of applications, setting engineering standards and shaping delivery. Works with C#, .NET, Python, Azure PaaS, SharePoint and React, collaborating with Product and Architecture, with an AI-native edge using GenAI tooling. Mainly remote with occasional Manchester office visits.

Carrington Recruitment Solutions · South Yorkshire · £80,000 – £90,000 pa

Hands-on full stack lead role guiding a small development team across a portfolio of applications, setting engineering standards while collaborating with Product, Architecture and wider technical groups. Work spans C#, .NET, Python, Azure PaaS, SharePoint and React, with an AI edge including GenAI tooling and taking experiments through to production-grade solutions.

Thought Machine · Singapore

Provides 24/7 global client support for a cloud-native core banking platform, triaging technical issues, reviewing logs, traces and observability dashboards, and performing initial diagnostics. Also provisions cloud infrastructure, runs product upgrades and releases, and works with L3 engineering and client success teams on root cause analysis.

Thought Machine · London

Technical Programme Managers own the delivery of complex, multi-team engineering programmes, from planning and milestones through to coordination and stakeholder communication. The role requires hands-on understanding of microservice stacks such as Kubernetes, Kafka and AWS/GCP, and involves driving continuous improvement across a fast-paced engineering organisation.

PhysicsX · Singapore

Join a new Singapore research team building physical foundation models for industrial engineering, translating physics challenges into mathematical formulations and training deep learning models on large datasets. You will own research workstreams, run experiments, and communicate results to customers and at publication venues, with a focus on operator learning, geometric deep learning, or generative models for geometry and spatiotemporal data.

eFinancialCareers · London

Lead a small, high-performing team of 6-7 engineers owning core ML infrastructure, including distributed model training, LLM hosting and fine-tuning, and scalable deployment systems. The role combines hands-on technical direction with people leadership, integrating advanced ML capabilities into production-grade, high-stakes systems. Suited to experienced engineering managers, not first-time managers.

Isomorphic Labs · London

Builds greenfield machine learning models and algorithms for drug discovery, designing new architectures, running experiments, and scaling training and inference frameworks. Works in an interdisciplinary team of ML scientists and domain experts, with opportunities to lead projects and mentor others depending on experience.

University of Oxford · Oxford · £39,424 – £43,984 pa

Develops 3D reconstruction and multi-view data fusion methods for neonatal cranial ultrasound, validating them on data from the neonatal intensive care unit. Works at the intersection of 3D computer vision, neural rendering and medical image analysis, including physics-informed rendering models for view-dependent acoustic appearance. Based in a multidisciplinary lab alongside deep learning researchers, software engineers and neonatologists.

The Alan Turing Institute · London · £96,000 – £115,000 pa

Provides scientific and strategic leadership for the AI for Physical Systems research area, shaping a portfolio spanning probabilistic modelling, uncertainty quantification, efficient architectures and physics-informed machine learning. Leads a multidisciplinary team of researchers and engineers, taking methods from foundational research through to deployment on real-world resilience challenges, and builds collaborations across academia, government and industry.

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.

University of Glasgow · Glasgow · £50,253 – £58,225 pa

Develops physics-informed machine learning and uncertainty quantification methods to improve subsurface characterisation for offshore wind and net-zero infrastructure. Joins an interdisciplinary team of engineers, data scientists and geophysicists within a UKRI-funded Fellowship, with scope to shape an ambitious research programme.

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.