Artificial Intelligence Jobs

Wayve · London

Build and operate a globally distributed Data Transfer Hub moving petabytes of video, LiDAR and sensor data per day between Wayve and partners such as Uber, Stellantis and Nissan. Write pipeline logic in Python, manage infrastructure with Terraform, and use Flyte, Kafka and Azure for orchestration, event-driven lifecycle tracking and storage. The small, high-autonomy team owns production reliability, observability and cost efficiency, with an out-of-hours on-call rotation once the service is established.

Wayve · London

Owns the technical vision and architecture for a platform that lets model engineers deploy, run, evaluate and improve ML models over petabytes of driving data and large GPU fleets. Combines hands-on backend engineering in Python with cross-team technical leadership, mentoring senior engineers and leading a small team of 2-3.

OpenAI · London

Builds data-intensive, AI-powered applications and infrastructure that help operators and investigators detect, triage and review high-severity harm, working across UIs, services and pipelines. Partners closely with the Child Safety team and cross-functional groups, owning systems end-to-end in an ambiguous, fast-moving environment. Involves exposure to sensitive and egregious content.

OpenAI · London

Partner directly with engineering organizations to design, build, and deploy AI-powered software development workflows using Codex, from use-case selection through prototyping, evaluation, and production rollout. Combines hands-on coding in Python with customer leadership, building evaluation harnesses, integrations, and reusable architectures while feeding deployment insights back to Product and Research teams.

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.

Faculty · London

Deliver bespoke, production-grade machine learning systems for government and national security clients, covering the full ML lifecycle from scoping and architecture to deployment. Work with Python, Scikit-learn, TensorFlow or PyTorch, plus cloud platforms and Docker/Kubernetes, while advising stakeholders and defining standards for deploying ML at scale.

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

Builds internal AI agents, tools and prototypes within a small central technical team, turning complex group data into usable products at speed. Work spans Python, TypeScript and SQL, modernising legacy systems, wrapping systems in scalable APIs and contributing to shared data and entity platforms, with weekly demonstrable output.

Ocado · Kraków, Poland

Senior ML engineer role in a cross-craft data science team building prediction, ranking and personalisation systems for an e-commerce platform. Owns the full ML lifecycle on production systems, from experimentation and training through serving, monitoring and MLOps, while coaching others and shaping reusable platform building blocks.

Humanoid · London

Hands-on engineering lead owning the path from AI agent task to healthy deployed change, building secure reproducible agent runtimes, verification tooling, and developer interfaces. Recruits and leads a new developer productivity team while working across Developer Tools, Security, Simulation, and robot software to cut cost and review time per accepted change.

Thought Machine · Lisbon, Portugal

Lead and develop a team of engineers while contributing technically to complex, cloud-native banking technology projects. Bridge product, client, and engineering teams to deliver scalable, secure solutions on a modern tech stack. Balance hands-on technical work with people management and strategic delivery in a fast-paced, high-ownership environment.

MFK Recruitment · Brentford · £70,000 – £95,000 pa

Design and deploy production-grade computer vision systems using deep learning techniques such as CNNs and Vision Transformers, translating research into robust AI solutions for defence and security applications. Work across the full development lifecycle, from model design and training to deployment on cloud and edge platforms. Collaborate with researchers, engineers, and customers in a technically challenging environment focused on real-world autonomy and perception systems.

Aioi Nissay Dowa Europe · United Kingdom · £81,322 – £112,488 pa

Dual role combining line management of a growing ML engineering team with hands-on technical delivery across multiple client projects. You'll shape ML engineering practice, lead multidisciplinary teams, oversee solution design and quality assurance, and support pre-sales and use case discovery alongside commercial teams.

Synthesia · London

Join the Voice team within a 40+ person R&D department to build human-interactive multimodal models combining text, audio and video. You'll define research roadmaps, propose novel architectures, develop low-latency streaming conversational systems, and take models from pretraining through post-training to production deployment.

Luminance · Cambridge

Join a small, dynamic R&D team prototyping and implementing new approaches to AI problems, evaluating output quality, efficiency and feasibility against other techniques in a data-driven way. Work spans data science on large datasets, modelling and evaluation, using Python ML frameworks such as PyTorch, TensorFlow and Scikit-Learn. Open to graduates as well as senior candidates with published work in NLP, Computer Vision or Deep Learning.

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.