3 of 3 Information Retrieval Jobs in the City of London

graph-connected AI applications. This is not a conventional data science role. You will work at the intersection of machine learning, semantic data modelling, information retrieval, knowledge graphs, and real-world construction product data. Your work will help turn fragmented industry data into reliable, contextual, and explainable decision … Computer Science, Data Science, AI, Software Engineering, Mathematics, Statistics, or a related field. 4+ years of hands-on experience in data science, machine learning, information retrieval, NLP, knowledge graphs, or related AI/data fields. Strong Python skills. Experience developing, testing, deploying, and monitoring data science or machine ...

credit teams. They are hiring a Founding Applied Research Engineer to join at early stage, with real ownership of the depth of knowledge and retrieval infrastructure . This role suits someone with a strong academic background from a leading university , alongside clear evidence of success in high ownership projects. … Experience with knowledge graphs and information retrieval is essential: Responsibilities Design knowledge graphs Build advanced information retrieval systems Create robust information extraction pipelines Translate research into production infrastructure On offer The opportunity to build a deep tech AI model and conduct original, applied research Founding ...

Design, build, and evaluate advanced AI/ML, NLP, and generative AI solutions for scientific and knowledge-discovery applications. Develop LLM-powered workflows and retrieval-augmented generation (RAG) systems for search, summarization, question answering, and evidence-grounded insight generation. Build intelligent retrieval, ranking, recommendation, and decision-support capabilities … scale. Provide technical leadership and mentoring to support high-quality delivery and continuous improvement. Requirements Practical experience in data science, AI, machine learning, NLP, information retrieval, or a related quantitative field. Strong hands-on experience building AI/ML, NLP, generative AI, and retrieval-based systems ...