4 of 4 Semantic Search Jobs in Manchester

vector databases and traditional data platforms. Model complex business domains to improve retrieval quality and contextual understanding. Design and optimise hybrid retrieval strategies using semantic search, keyword search, embeddings and knowledge graphs. Evaluate, integrate and extend best-of-breed tooling rather than building infrastructure unnecessarily. Measure, monitor … scalable knowledge systems for AI-powered applications. Strong understanding of domain modelling, ontology design and information architecture. Hands-on experience with hybrid retrieval techniques, semantic search, embeddings and vector databases. Experience building reliable data pipelines and integrating multiple data sources. Excellent judgement in selecting the right technologies ...

Databricks or similar technologies Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps ...

role: - Design AI and GenAI architecture strategies and roadmaps - Build scalable AI/ML and Agentic AI platforms - Work across LLMs, RAG, embeddings and semantic search - Support AI deployment, governance and integration patterns - Collaborate with engineering, data, DevOps and business teams - Advise clients on AI platform capability ...

mitigating hallucinations and output errors. Deploy and maintain RAG architecture and LLM pipelines within cloud environments. Optimise data-chunking and text embeddings for optimal semantic search across a large, specialist corpus. Track the competitive landscape and stay current with technological advancements in GenAI. Monitor and optimise agent ...