7 of 7 Semantic Search Jobs in the UK excluding London

APIs and microservices that handle real-time threat analysis at scale Implement computer vision systems for image and video analysis in OSINT investigations Build and optimize vector databases for semantic search across massive intelligence datasets Establish best practices for AI/ML model deployment, monitoring, and continuous improvement Mentor team members on AI engineering practices and drive technical More ❯

APIs and microservices that handle real-time threat analysis at scale Implement computer vision systems for image and video analysis in OSINT investigations Build and optimize vector databases for semantic search across massive intelligence datasets Establish best practices for AI/ML model deployment, monitoring, and continuous improvement Mentor team members on AI engineering practices and drive technical More ❯

Experience identifying AI use cases and translating them into business value Preferred Experience with LibROSA, Essentia, or other audio analysis libraries Knowledge of computational musicology and MIR Familiarity with semantic search, vector databases, and explainable AI Understanding of music licensing and rights management Background in retail tech or B2B SaaS is a plus What We Offer A unique More ❯

languages. Strong SQL and data analytics skills. Familiarity with cloud platforms (AWS and Azure) for AI deployment. Knowledge of MLOps principles for scaling AI models. Understanding of knowledge graphs, semantic search, and vector databases. AI Ethics and Responsible AI Awareness of AI ethics, bias mitigation, and fairness in models. Understanding of GDPR and compliance frameworks for AI in More ❯

LEAD AI ENGINEER LIVERPOOL 2 DAYS ON-SITE INSIDE IR35 A hands-on, innovation-driven role focused on rapidly prototyping advanced AI systems using LLMs, autonomous agents, and semantic search. The engineer will work across the full stack-from prompt engineering and memory management to UI and cloud deployment-using tools like LangChain, CrewAI, and vector databases. Core Responsibilities More ❯

workflows that leverage tool usage and chaining Experiment with, tune, and benchmark different LLMs (e.g., OpenAI, HuggingFace, LangChain) Automate model evaluation and integrate insights into the dev lifecycle Support semantic search, data extraction, and document analysis use cases Collaborate with legal engineers and product to build secure and compliant AI systems Contribute to architectural decisions, internal tooling, and … APIs and cloud infra is a plus Proven track record designing evaluation frameworks and tuning model performance Solid understanding of data privacy, system integrity, and scalable architecture Experience with semantic search, retrieval pipelines, or document-based AI systems is a bonus Nice to Have: Exposure to legal tech, compliance tools, or privacy-centric workflows Familiarity with ML frameworks More ❯

data pipelines, and MLOps practices. Experience with Azure services such as Azure Machine Learning, Azure Data Factory, Azure Synapse, and Azure Functions. Implementing modern retrieval techniques such as vector search, semantic search and Retrieval-Augmented Generation (RAG) using tools like Azure Cognitive Search, FAISS, Pinecone, or Weaviate. Familiarity with data governance, privacy, and ethical AI principles. More ❯