Artificial Intelligence Jobs

OpenAI · London

Lead and grow a London-based engineering team building real-time safety and oversight systems for AI agents, including the Auto-review permission-boundary model. The role blends hands-on technical work—shaping architecture, reviewing designs, debugging, and coding—with hiring, coaching, and setting the operating cadence. It is highly cross-functional, partnering with alignment researchers, product, security, and infrastructure teams.

Luminance · London

This is a fantastic opportunity to join Luminance, the pioneer of Legal-Grade™ AI for enterprise. Backed by internationally renowned VCs and named in both the Forbes AI 50 list of ‘Most Promising Private AI Companies in the World’ and Inc....

Faculty · London

Associate role in the National Security and AI Safety business unit, managing work streams to deliver bespoke AI solutions for government and intelligence clients. Involves open-source analysis, translating operational requirements into user stories, and designing workflows for high-stakes decision-making alongside technical teams. May require UK Developed Vetting eligibility and occasional on-site client work.

OpenAI · London

Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training workloads, identifying slow or faulty nodes and surfacing performance bottlenecks. Work deep in the stack across collective communication, parallelism, fault tolerance, and observability, collaborating with systems, infrastructure, and research teams to evolve the training platform.

NVIDIA · Bristol

Research and develop techniques to GPU-accelerate deep learning, machine learning and other AI workloads, working with technical experts from industry and academia to analyse and optimise complex AI and HPC algorithms on modern CPU and GPU architectures. The intern also publishes optimisation techniques via developer blogs or conferences and helps influence next-generation hardware, software and programming models.

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.

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.

Wayve · London

Develops embedded software connecting an AI Driver to vehicle steering, braking and propulsion systems, working hands-on with benches and vehicles. Involves MATLAB/Simulink development, drive-by-wire actuation logic, CAN/CAN-FD diagnostics, OTA updates and ADAS/HMI interfaces, collaborating with OEMs, suppliers and controls engineers.

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.

University of Sheffield · Sheffield · £39,560 – £43,099 pa

Postdoctoral role applying explainable NLP and machine learning to analyse online disinformation narratives, integrate findings into a user-facing verification toolkit, and evaluate commercial chatbots and AI-generated search overviews. The researcher joins the European-funded ANTIGONE project, collaborating with multidisciplinary partners and leading publication of results in high-impact journals and conferences.

The University of Manchester · Manchester · £48,337 – £59,390 pa

Develops and applies machine-learning and AI methods to protein engineering and enzyme design, analysing large biological, chemical and experimental datasets and building predictive models and computational tools. Works within an interdisciplinary group spanning the Manchester Institute of Biotechnology and Department of Chemistry, providing ML and data-science expertise, training and support to postdocs and students, and contributing to publications and funding bids.

University of Exeter · Exeter · £21,805 pa

An interdisciplinary PhD co-designing miniaturised, low-power sensing hardware with AI for field-based wildlife monitoring, including individual recognition and automated behaviour quantification. Systems are benchmarked in controlled conditions then validated on wild jackdaws and West African field sites, spanning behavioural ecology, electronic engineering and data science.

Jam Management Consultancy ltd · Reading · £35,000 – £38,000 pa

Graduate role investigating and resolving technical issues across enterprise software platforms, analysing system performance and supporting troubleshooting on cloud-based applications. Works alongside experienced engineers on analysis, testing and continuous improvement, with exposure to AI, ML, NLP, SaaS, IoT and languages including Python, C#, .NET, Java, JavaScript, TypeScript, React, C++ and SQL.

eFinancialCareers · London

Leads the design, development and operation of high-rigor analytical and machine-learning systems across a complex, regulated financial-services estate, defining the AI/ML roadmap while remaining hands-on. Owns the full model lifecycle from feature engineering and back-testing to deployment, monitoring and incident response, with models expected to be explainable and production-grade. Works closely with engineering, data platform and product teams, mentoring other data scientists with limited line management.

eFinancialCareers · London

Develops predictive machine learning models for fixed income and credit markets, covering issuer credit deterioration, transaction costs, liquidity forecasting and relative-value opportunities. Also builds LLM-powered document intelligence systems to extract structured data from filings, transcripts and prospectuses, with a strong emphasis on out-of-sample validation, explainability and production data pipelines.