Artificial Intelligence Jobs

Hadean · London

Lead a multidisciplinary engineering team building dominAI, an AI-powered defence product, line-managing AI/ML, simulation, infrastructure and web engineers while staying hands-on in TypeScript, React and Node. Own delivery end-to-end, hiring and people development, partnering with Product and technical leads. Hybrid, one day a week in Shoreditch.

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.

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

Hands-on full stack engineering role guiding a small development team while collaborating with Product and Architecture. You will build and shape delivery standards across C#, .NET, Python, Azure PaaS and React, with an AI edge using GenAI tools and taking experiments to production. Mainly remote with occasional Birmingham office visits.

Wayve · London

Owns shared onboard runtime foundations for autonomous vehicles: application frameworks, communication middleware, lifecycle management, health monitoring and observability. Day to day involves C++ development, end-to-end latency and performance profiling across OS scheduling, memory hierarchy and thread synchronisation, plus porting the stack to new operating systems and compute platforms.

Infused Solutions · London · £65,000 – £75,000 pa

Hands-on full-stack role building brand-new AI-powered products from concept to production within a small, senior engineering team. You'll architect scalable solutions, develop PoCs, prototypes and MVPs, build React UIs and Node.js/Express/Python APIs on Azure, and use AI-assisted development tools to accelerate delivery.

Databricks · London

Customer-facing role building and productionising data and AI solutions on the Databricks platform, owning architecture and design decisions for end-to-end systems spanning data engineering, ML/AI and application development. Embeds with client teams from engineers to executives, delivering production-grade reference architectures and reusable accelerators, with around 20% travel.

Quantexa · London

Builds and enhances scoring and detection tooling on Quantexa's Decision Intelligence platform, turning complex interconnected data into insights for financial crime detection. Works across the stack with agentic AI tooling, taking features from concept to release alongside product teams and senior engineers.

PhysicsX · London

Owns and evolves an HPC environment for CPU/GPU-heavy physics simulations, covering cluster administration, job scheduling (Slurm/PBS/LSF), performance tuning and capacity planning. Acts as escalation point across HPC, developer tooling and general IT support, mentors junior engineers, and drives automation-first, zero-trust infrastructure in a scale-up.

Thought Machine · Lisbon, Portugal

Owns complex, ambiguous technical challenges end-to-end, shaping long-term platform architecture and company-wide engineering standards. Drives adoption of AI tooling, leads technical interviews, and mentors senior engineers while acting as a link between leadership and engineering teams. Based in the Lisbon office, requiring three days a week onsite.

Entrust · London

Builds and operates production ML systems for document classification and extraction, using LLMs/VLMs and traditional ML to process government identity documents at scale. Owns features from RFC through deployment, optimising GPU inference and training/evaluation pipelines, and mentors engineers within a squad-based team.

Entrust · Lisbon, Portugal

Builds and operates production ML systems for document classification and extraction, using VLM/LLMs and traditional ML to power identity verification for millions of users. Leads technical design from RFC to deployment, optimises GPU inference, and designs training, evaluation and labelling pipelines. Works in a squad-based team alongside Applied Science, Product and Data Science, mentoring engineers and driving reliability and scalability.

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.

NVIDIA · United Kingdom

Lead architecture for cloud-networking, defining system architecture for DPUs and NICs across orchestration, provisioning, security and SDN. The role spans application to hardware level, writing architecture specifications and building POC prototypes, while working with global SW/HW architects, R&D and high-profile customers.

Isomorphic Labs · London

Research engineers translate frontier research concepts into practical implementations, building and optimising state-of-the-art AI models such as Transformers, GNNs and diffusion models, plus the codebases, data pipelines and infrastructure for training and evaluation. They design and run experiments, analyse model performance, and advise on bringing models to production, working closely with research scientists in a cross-disciplinary team.

Scale AI · London

Builds full-stack AI applications directly alongside public sector clients, scoping requirements, gathering feedback and shipping production-grade systems. Work spans React and TypeScript front ends, Python/Node backends, and cloud infrastructure on AWS, Azure or GCP, with a focus on reusable platform features and deploying into customer environments.

PhysicsX · New York, United States · US$150,000 – US$250,000 pa

Builds and deploys customer-facing applications on top of physics AI models, working directly with clients, data scientists and ML engineers. Involves full-stack work: FastAPI REST APIs and Python microservices, plus cloud deployment with Helm, Kubernetes, Terraform and AWS/Azure. Expect on-site travel to customer sites for 3-4 weeks per quarter.