Artificial Intelligence Jobs

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

You will own and evolve the internal delivery platform that supports over 100 data scientists and ML engineers, building MLOps, data science and deployment tooling. Day to day involves infrastructure-as-code, DevSecOps, containerised microservices and integrating core services across AWS, Azure and GCP. The role sits in a small, fast-moving team focused on removing technical friction for customer-facing delivery teams.

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 · 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.

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.

PhysicsX · New York, United States · US$120,000 – US$240,000 pa

Builds and deploys deep learning and probabilistic models to predict and control physical systems, working alongside simulation and ML engineers. Owns data pipelines and production deployment, and collaborates directly with customers on-site across multiple regions. Based in Manhattan with 2-3 days per week in office and frequent travel.

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.

Experis · United Kingdom · £400 – £500 pd

Multiple contract roles spanning data, ML and AI platform engineering, from hands-on specialists to technical leads. Work covers architecture, engineering, governance, security, reliability and operations on a large-scale modern environment, using Python, SQL, Go, DataHub, Trino/Starburst, JupyterHub, OpenSearch, Entra ID/OIDC, FluxCD/Argo CD and Helm. Remote and global, with rates negotiable by experience and location.

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.

Isomorphic Labs · London

Translates Isomorphic Labs' security strategy into engineering delivery, steering a multi-quarter InfoSec roadmap spanning Cloud Security, Platform IAM and Secure SDLC. Partners directly with engineering and ML teams to unblock architectural issues, secure drug discovery pipelines and build data-driven dashboards giving the CISO visibility into program health and risk metrics. Reports to the CISO with a functional tie to the TPM Discipline Lead.

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.

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.

VIQU IT · Cornhill, Greater London · £90,000 – £95,000 pa

Owns the end-to-end architecture of an enterprise AI platform spanning Azure and AWS, covering ML training, model hosting, MLOps and Generative AI. Defines patterns for LLMs, RAG, vector search and agent frameworks, evaluates tooling, and provides technical direction to ML and platform engineers while embedding security, governance and regulatory requirements.