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.

Matchtech · Cambridgeshire · £450 – £650 pd

Contract Python developer role focused on building and maintaining software for integration with a defence cloud environment. Day-to-day work spans data and AI, automation and tooling, and DevOps, using Red Hat OpenShift, Quay, HashiCorp Vault, Tekton Pipelines, GitHub, ArgoCD and SonarQube within agile teams. Requires UK Eyes Only clearance eligibility and is based on-site/hybrid in Cambridgeshire.

Darktrace · Cambridge

Partners with developers and product teams to embed quality from the start, designing and maintaining automated test frameworks across API, UI, integration and regression layers. Builds scalable suites into CI/CD pipelines, drives shift-left testing, and contributes to test strategy, code reviews and architecture discussions.

OpenAI · London

Builds and operates the platform that deploys, configures and manages models across ChatGPT, spanning deployment orchestration, rollouts, operational automation and capacity management. Works with research, infrastructure and product teams to turn complex operational processes into reusable, scalable platform capabilities, with a focus on reliability, observability and developer experience.

eFinancialCareers · London · £450 – £550 pd

Develops and maintains C# software and algorithms that process incoming news streams, turning financial and market data into accessible information for research and investment decisions. Also explores artificial intelligence to enhance information processing and contributes to the wider software infrastructure supporting Global Research services. Works alongside Python-based tooling within a consultancy team serving financial services clients.

Wayve · London

Develops and maintains Wayve's Core Simulation system in modern C++ and Python, integrating driving-stack components, simulated robot systems and vehicle-platform capabilities. Initially focused on high-scale open-loop evaluation, the role involves debugging on-road versus simulated behaviour, improving reproducibility, observability and automated testing, and profiling simulator performance across a shared codebase.

Quantexa · London

Builds and enhances scoring and detection tooling on a Decision Intelligence platform, turning complex interconnected data into actionable 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.

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.

Databricks · London

Customer-facing engineering role building and productionizing data and AI solutions on the Databricks platform for emerging enterprise and digital native accounts. You own architecture and design decisions, implement end-to-end systems spanning data engineering, ML/AI and application development, and embed with client teams. Billable delivery work with roughly 20% travel.

OpenAI · London

You'll partner with early-stage startups to embed Codex into their software workflows, building integrations, automations and reusable tools while troubleshooting technical blockers. A large part of the role is outward-facing: leading technical talks, live demos, workshops and hackathons, then feeding developer insights back to OpenAI's product and research teams.

Wayve · London

You'll design, build and operate shared infrastructure for model access, agent runtimes and observability, taking projects from problem definition through technical design, deployment and ongoing operation. Working with security, IT and engineering teams, you'll create governed access layers, reusable tooling and standards so teams can run AI agents in production without one-off infrastructure.

Scale AI · London

Leads a forward-deployed engineering team acting as the technical bridge between AI capabilities and strategic enterprise customers. Involves designing custom integrations, ETL pipelines and production AI agents, plus prompt engineering, RAG systems and evaluation frameworks, deployed within customer security and compliance boundaries.

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.

Profile 29 · Witney · £45,000 – £65,000 pa

Design and develop safety-critical embedded software for autonomous systems, building runtime assurance and fail-safe architectures using SPARK Ada and high-integrity processes. Work spans verification, validation and certification activities for DAL-A/DAL-B software across aerospace and land autonomy platforms, scaling prototype capability to enterprise deployment.

ElevenLabs · London

Embedded with strategic customers, you design tailored technical architectures, build full-scale integrations and take end-to-end ownership of high-impact projects. Working daily with customer engineers and executives, you use Python and API integration skills to solve complex problems. Remote-first across the UK, with a London office option and regular customer travel.

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.