Artificial Intelligence Jobs

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.

PhysicsX · New York, United States · US$150,000 – US$190,000 pa

Delivery-focused role embedding physics-aware AI models into customer tools, working on-site with clients across aerospace, automotive and energy. Involves building reliable ML data pipelines, manipulating 3D point-cloud and mesh data, and translating R&D outputs into reusable libraries and products. Expects travel of 3-4 weeks per quarter to customer sites worldwide.

Harnham - Data and Analytics Recruitment · Abingdon · US$200,000 – US$225,000 pa

Build scalable data platforms, pipelines and ML infrastructure, and deploy production AI solutions including LLMs, RAG systems and AI agents. Work in a small, highly visible team partnering with investment and operational stakeholders, owning projects end-to-end from design through production and driving architecture decisions.

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.

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.

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.

Adria Solutions · Huddersfield · £55,000 – £70,000 pa

Develops software and applied AI models for machine vision, working across C++, C# and Python to build image-processing algorithms and integrate models into reliable applications. Involves dataset preparation, model evaluation, performance tuning for accuracy and inference speed, automated testing and debugging of vision pipelines. Hybrid or remote, with a path to lead an AI team.

Isomorphic Labs · London

Join the model performance and scaling team to implement and optimize LLM post-training methods on frontier models, collaborating with research teams to turn new methods into production-ready systems. The role focuses on distributed training and inference performance, low-precision methods, and frameworks like JAX or PyTorch, in a hybrid London setting.

Adria Solutions · Huddersfield · £35,000 – £45,000 pa

Supports AWS infrastructure, CI/CD pipelines and automation for software and machine learning workloads, including packaging, versioning and deploying ML models. Works alongside software and AI engineers to keep development, testing and production environments consistent, monitoring pipelines and fixing issues. Suited to an early-career engineer with cloud, scripting and Git foundations and an interest in MLOps.

Tech Recruitment Specialists Ltd · London · £38,000 – £45,000 pa

Supports the development, optimisation and deployment of AI and machine learning models, working with large datasets for preprocessing and training, and helping monitor AI applications in production. Collaborates with software engineers, product teams and data specialists, contributes to backend development and API integrations, and researches new AI frameworks. Emphasis on responsible, ethical AI with bias mitigation, transparency and fairness.

Harnham - Data and Analytics Recruitment · London · £80,000 – £85,000 pa

Design, build and deploy scalable AI and machine learning solutions from concept to production, including Generative AI applications using LLMs and orchestration frameworks. Write production-grade Python, apply MLOps practices such as CI/CD, containerisation and monitoring, and build data pipelines for training, fine-tuning and inference. Work hybrid in London alongside data scientists, engineers and business stakeholders on large-scale datasets.

Relation Therapeutics · London

Join the Platform Team to design and scale Kubernetes-based hybrid compute clusters across private and public clouds, building core platform services and APIs. You will own CI/CD pipelines, monitoring, backup and disaster recovery, and work closely with Machine Learning and Data Science teams to support their computational needs.

Anthropic · London

Conduct experimental research on AI safety, focusing on alignment and robustness of advanced systems. Develop and test techniques like AI debate and jailbreak evaluation, contributing to publications and safety policy. Work in a collaborative, interdisciplinary team using machine learning and systems engineering.

Corecom Consulting · Belfast · £25,500 pa

A two-year academy programme for career changers with no prior experience or degree, combining full-time hybrid training with client project work. Trainees cover Agile, SQL, APIs, Python, testing, data science and AI/ML, then work as an AI Engineer and Software Quality Engineer on real client projects.

PhysicsX · London

Builds the simulation side of Large Physics Models, generating multi-fidelity CFD data to train large-scale ML models. Develops solvers and numerical methods in differentiable or GPU-native frameworks such as JAX or NVIDIA Warp, using commercial and open-source CFD tools for reference data. Works in a research team alongside ML researchers, shaping data generation strategy and fidelity tradeoffs.

Speechmatics · Cambridge

Own the infrastructure behind speech AI models: building scalable data pipelines for ingesting, transforming and validating large training datasets, plus web scraping and automated data acquisition. Also operates the platform for training, evaluating and serving models, optimising GPU utilisation, scheduling and observability across distributed systems.