14 of 14 Question Answering Jobs in the UK

experience in industry. Commercial experience in applying NLP, LLM and ML techniques in solving high-impact business problems, such as semantic search, information extraction, question answering, personalisation, classification, recommendation or forecasting. Advanced python programming skills with experience writing production quality code using ML libraries and deep learning frameworks. ...

solutions and translating emerging AI techniques into impactful product capabilities. Key responsibilities Applied AI & Research Develop and improve LLM-based research workflows, including:Scientific question answeringLiterature summarizationSemantic exploration and discoveryResearch insight generationCitation-aware retrieval and reasoning workflows Build and iterate on agentic and multi-step AI workflows using frameworks ...

enterprise by providing shared platforms, patterns, governance, and delivery support. CE AI owns and operates core AI platforms including LSEG AI Assist, the Question Answering Service (QAS), and the Internal MCP Gateway. Rather than delivering individual business use cases end‐to‐end, the team enables product engineering groups ...

enterprise by providing shared platforms, patterns, governance, and delivery support. CE AI owns and operates core AI platforms including LSEG AI Assist, the Question Answering Service (QAS), and the Internal MCP Gateway. Rather than delivering individual business use cases end‐to‐end, the team enables product engineering groups ...

enterprise by providing shared platforms, patterns, governance, and delivery support. CE AI owns and operates core AI platforms including LSEG AI Assist, the Question Answering Service (QAS), and the Internal MCP Gateway. Rather than delivering individual business use cases end‐to‐end, the team enables product engineering groups ...

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 using modern orchestration frameworks and AI techniques. Integrate scientific metadata ...

enterprise by providing shared platforms, patterns, governance, and delivery support. CE AI owns and operates core AI platforms including LSEG AI Assist, the Question Answering Service (QAS), and the Internal MCP Gateway. Rather than delivering individual business use cases end‐to‐end, the team enables product engineering groups ...

enterprise by providing shared platforms, patterns, governance, and delivery support. CE AI owns and operates core AI platforms including LSEG AI Assist, the Question Answering Service (QAS), and the Internal MCP Gateway. Rather than delivering individual business use cases end‐to‐end, the team enables product engineering groups ...

GenAI capabilities across IDBS platforms. Essential requirements Designing, building, and operating LLM-powered capabilities such as document summarisation, retrieval augmented generation (RAG), and question answering over enterprise datasets. Developing AI‐ready data foundations, including unstructured data pipelines, metadata extraction and enrichment, and hybrid architectures using vector stores alongside ...

enterprise by providing shared platforms, patterns, governance, and delivery support. CE AI owns and operates core AI platforms including LSEG AI Assist, the Question Answering Service (QAS), and the Internal MCP Gateway. Rather than delivering individual business use cases end‐to‐end, the team enables product engineering groups ...

enterprise by providing shared platforms, patterns, governance, and delivery support. CE AI owns and operates core AI platforms including LSEG AI Assist, the Question Answering Service (QAS), and the Internal MCP Gateway. Rather than delivering individual business use cases end‐to‐end, the team enables product engineering groups ...

discovery algorithms to find root causes in complex manufacturing data Design and implement agentic RAG (retrieval, ranking and context selection) methods to support enterprise question-answering Build document-intelligence pipelines to extract and cross-check information from drawings, specifications and unstructured documents (Discrepancy AI) Implement robust connectors ...

assisted workflows, feeding findings into design and product decisions. Interaction Design for AI Workflows Design end-to-end user journeys for RAG-based question‐answering, agentic workflows, and human‐in‐the‐loop review steps, ensuring users understand what the AI is doing, where information comes from, and when ...

users and stakeholders to understand tasks, pain points, and trust concerns around AI-assisted workflows Design end-to-end user journeys for RAG-based question-answering, agentic workflows, and human-in-the-loop review steps Ensure users understand what the AI is doing, where information comes from ...