Artificial Intelligence Jobs

Faculty · London

Build and scale AI-powered systems for public sector clients, owning the full stack from Python/FastAPI backends to TypeScript and React or Vue frontends. Work in cross-functional teams with data scientists and product managers, deploying to AWS, Azure or GCP with Docker and building data pipelines and cloud infrastructure. May require UK Security Clearance and occasional on-site work with government clients.

Faculty · London

Builds and deploys production-grade ML software, tools and infrastructure, creating reusable solutions that accelerate ML delivery and capability testing of frontier AI models. Leads technical scoping and architectural decisions, advises clients and partners, and works with frontier labs on AI safety red teaming and evaluation.

Carrington Recruitment Solutions · London · £95,000 – £105,000 pa

Hands-on lead role guiding a small development team across a portfolio of applications in a highly regulated professional services environment. Involves C#, .NET, Python and Azure PaaS work, with a strong AI focus spanning GenAI tools, Co-Pilot Studio and taking experiments through to production-grade solutions, while shaping delivery and engineering standards alongside Product and Architecture.

Ncounter · Reading · £120,000 – £140,000 pa

Hands-on engineering leadership role overseeing a multidisciplinary team of software, platform and DevOps engineers. You'll own technical architecture and standards across cloud-native applications, AI/ML platforms and MLOps, while remaining close to delivery and shaping longer-term technical strategy for National Security and Defence customers.

Databricks · United Kingdom

Customer-facing technical authority on Generative AI, LLMs and applied ML for digital-native and startup accounts across EMEA. Shapes architectures, builds hands-on proofs of concept and reference implementations on Databricks (Mosaic AI, MLflow, Model Serving, Vector Search, Unity Catalog), and leads fine-tuning and evaluation engagements on open models. Also mentors the field engineering organisation and represents the company externally through talks and blogs.

University of East Anglia · Norwich · £21,805 pa

A PhD studentship developing multispectral and hyperspectral imaging combined with machine learning to detect and classify marine litter from aerial and drone-based platforms. The researcher will characterise litter material reflectance in the lab, curate imaging datasets, and build models robust to changing illumination and sensor differences, based in the Colour & Imaging Laboratory and working with CEFAS scientists.

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.

Helsing · Barcelona, Spain

PhD research internship tackling open problems in spatial perception and localisation within the Spatial Intelligence Team. You survey and prototype state-of-the-art methods for scene matching, SLAM/VIO and 3D reconstruction, benchmarking ideas against real-world data and compute constraints, and report findings to a Europe-distributed team.

Mohamed bin Zayed University of Artificial Intelligence · Abu Dhabi, United Arab Emirates

Conducts AI and network data science research on molecular multi-omics and medical data to advance precision medicine and discover new therapeutics. Works with an interdisciplinary team on the flagship Human Phenotype Project and Emirati Genome Project datasets, designing algorithms, publishing papers, and helping supervise PhD and MSc students.

Wayve · London

Lead the Applied Methods Data Science team, partnering with the Autonomy organisation to turn experimental and observational analysis of real and simulated driving into evaluations and insights. Set three-, six- and 12-month roadmaps, review technical proposals for statistical rigour, hire and grow data scientists, and build tooling to scale the team's capability.

eFinancialCareers · Belfast

Hands-on player-manager role leading a growing Data & Analytics function, combining Power BI development, SQL analysis and AI exploration with stakeholder management and delivery leadership. You will build dashboards and semantic models, manage the Power BI environment and backlog, prototype HTML-based analytical applications, and apply generative AI and Copilot to improve reporting while coaching analysts and engineers.

Wayve · London

Owns the technical architecture and roadmap for LiDAR and cross-sensor 3D sensing, developing calibration, registration, temporal alignment and motion compensation methods. Blends algorithm research with production deployment in C++/Python, providing technical leadership and mentorship across the 3D sensing stack.

University of Sheffield · Sheffield · £32,080 pa

Build and evaluate machine learning models that predict Strep A outbreak risk from multiple real-world datasets, turning them into early-warning signals. Work with clinicians and an engineering team so analyses feed into a practical public health tool, with a focus on reproducible Python and/or R analysis.

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.

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.