As a Senior AI Engineer at PoliceAI, you will lead the design, development, and deployment of AI-enabled products, translating policing needs into technical solutions. You will work with multidisciplinary teams to build secure, maintainable, and scalable services, and support the testing, evaluation, and validation of AI products.
As Head of AI, you will lead the development and implementation of AI strategies, governance, and capabilities at LPPA, a leading pension administration company. You will work closely with the CTO and executive team to identify and deliver AI opportunities that enhance operational efficiency, service quality, and member outcomes. Key responsibilities include building the AI team, establishing governance frameworks, and fostering AI adoption across the organization.
This role involves leading a small development team in a fast-growing professional services company, focusing on full-stack engineering with a Microsoft stack. Responsibilities include hands-on coding, setting technical standards, collaborating with product and architecture teams, and integrating AI technologies into solutions.
This role involves hands-on full stack development, primarily using .NET, C#, and Azure technologies. You will lead a small team, set engineering standards, collaborate with product and architecture teams, and explore AI and machine learning applications.
This PhD studentship focuses on developing vision-language models (VLMs) to improve micro-expression analysis by combining subtle facial motion recognition with language-based reasoning. The research aims to create explainable, multimodal AI systems that can detect, describe, and justify micro-expression predictions using structured language representations. The project advances human-centred AI with applications in affective computing and healthcare.
Develop a physics-informed neural network-based computational fluid dynamics simulator for offshore renewable energy applications, integrating deep learning with fluid dynamics models and embedding the solution into OpenFOAM. The role combines PhD research with teaching, focusing on improving simulation efficiency and robustness for complex engineering problems.
This role involves developing machine learning tools to investigate catalytic reaction mechanisms, focusing on homogeneous catalysis in organic chemistry. The researcher will work collaboratively with the Bures group at ICIQ, building on published proof-of-principle work. The position is based in the Department of Chemistry at the University of Manchester and supports a 24-month EPSRC-funded project.
This PhD studentship focuses on developing AI-enhanced flexible antenna systems for next-generation wireless networks, specifically targeting 6G technologies. The research will explore AI-driven methods for channel estimation, beamforming, and real-time network optimisation to improve system resilience, energy efficiency, and coverage in dynamic environments. The candidate will work within a research group at The University of Manchester, contributing to cutting-edge advancements in wireless communication systems.
This role involves collaborating with teams to secure AI and Machine Learning solutions, conducting threat modelling, and ensuring compliance with security standards. The position offers exposure to cutting-edge AI technologies and a dynamic, collaborative environment.
This role involves hands-on technical work, including architecture, development, and delivery of features across the full stack. You will mentor other engineers, improve CI/CD processes, and integrate AI/LLM functionality where it adds value.
This role involves leading enterprise AI transformation, advising C-suite stakeholders, designing human-centred AI solutions, and establishing responsible AI practices. You will work with major organisations to embed AI technologies and drive commercial growth while building and developing high-performing teams.
This role involves leading business analysis activities in an AI-enabled transformation environment, facilitating stakeholder workshops, assessing AI opportunities, and designing future-state processes. The focus is on practical application and measurable outcomes, with a strong emphasis on stakeholder engagement and independent operation.
This role involves designing, developing, testing, and deploying front-end and back-end components of Generative and Agentic AI applications. You will work with a tech-obsessed team, translating complex business challenges into AI-powered solutions and collaborating with cloud architects, data scientists, and product managers to take ideas from concept to production.
This role involves building production applications and APIs using Python and FastAPI, developing LLM, RAG, and AI agent solutions, and working with vector databases. You'll collaborate with engineers, architects, and client stakeholders to take GenAI POCs into production and scale them.
This role involves designing and owning cloud-native data platforms for Defence, Government, and National Security clients. You'll work with big, messy, multi-source datasets, building scalable data lakes and pipelines on AWS or Azure, and collaborating closely with data scientists, software engineers, and architects.
This role involves developing and deploying machine learning and NLP models for intelligence data, working closely with end users in a multi-disciplinary team. Responsibilities include pattern detection, data matching, anomaly spotting, and building production-ready data and ML pipelines.
This role involves designing and building scalable data pipelines, integrating data from multiple sources, and developing AI and machine learning models. You will work closely with analysts and business stakeholders to translate requirements into robust technical solutions, while contributing to data quality, governance, and performance optimization.
