26 to 50 of 82 Semantic Search Jobs in the UK

for short-term and long-term agent behaviours. • Deploy models and orchestrate AI systems on cloud platforms such as AWS Bedrock, Google Vertex AI, and Azure AI Studio. • Integrate semantic search strategies and embeddings to improve LLM relevance and contextual understanding. • Build demo-ready user interfaces with tools like Streamlit, Gradio, or React. • Develop and maintain robust APIs … credibility with Google - experience working collaboratively with their teams, Google Premier Cloud Partner experience etc • Proven track record designing and deploying agentic and generative AI prototypes. • Deep understanding of semantic search, vector databases, and memory management strategies. • Familiarity with cloud AI tools, observability platforms, and performance optimisation. This is an opportunity to work at the forefront of AI More ❯

for short-term and long-term agent behaviours. • Deploy models and orchestrate AI systems on cloud platforms such as AWS Bedrock, Google Vertex AI, and Azure AI Studio. • Integrate semantic search strategies and embeddings to improve LLM relevance and contextual understanding. • Build demo-ready user interfaces with tools like Streamlit, Gradio, or React. • Develop and maintain robust APIs … credibility with Google - experience working collaboratively with their teams, Google Premier Cloud Partner experience etc • Proven track record designing and deploying agentic and generative AI prototypes. • Deep understanding of semantic search, vector databases, and memory management strategies. • Familiarity with cloud AI tools, observability platforms, and performance optimisation. This is an opportunity to work at the forefront of AI More ❯

for short-term and long-term agent behaviours. • Deploy models and orchestrate AI systems on cloud platforms such as AWS Bedrock, Google Vertex AI, and Azure AI Studio. • Integrate semantic search strategies and embeddings to improve LLM relevance and contextual understanding. • Build demo-ready user interfaces with tools like Streamlit, Gradio, or React. • Develop and maintain robust APIs … credibility with Google - experience working collaboratively with their teams, Google Premier Cloud Partner experience etc • Proven track record designing and deploying agentic and generative AI prototypes. • Deep understanding of semantic search, vector databases, and memory management strategies. • Familiarity with cloud AI tools, observability platforms, and performance optimisation. This is an opportunity to work at the forefront of AI More ❯

with domain-specific knowledge. Prompt engineering and fine-tuning for tailoring model behavior to business-specific contexts. Use of embedding stores and vector databases (e.g., Pinecone, Redis, Azure AI Search) to support semantic search and recommendation systems. Building intelligent features like AI-powered chatbots , assistants , and question-answering systems using LLMs and conversational agents. Awareness of agentic … AI concepts — orchestrating multiple agents with specific tasks/goals in a collaborative, dynamic environment. Familiarity with tools and frameworks that enable LLM-based integrations such as LangChain , Semantic Kernel , or Azure OpenAI . Appreciation for ethical AI considerations including data privacy , security , and bias mitigation . Eagerness to explore emerging technologies and collaborate with AI/ML teams More ❯

with domain-specific knowledge. Prompt engineering and fine-tuning for tailoring model behavior to business-specific contexts. Use of embedding stores and vector databases (e.g., Pinecone, Redis, Azure AI Search) to support semantic search and recommendation systems. Building intelligent features like AI-powered chatbots , assistants , and question-answering systems using LLMs and conversational agents. Awareness of agentic … AI concepts — orchestrating multiple agents with specific tasks/goals in a collaborative, dynamic environment. Familiarity with tools and frameworks that enable LLM-based integrations such as LangChain , Semantic Kernel , or Azure OpenAI . Appreciation for ethical AI considerations including data privacy , security , and bias mitigation . Eagerness to explore emerging technologies and collaborate with AI/ML teams 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 ❯

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 ❯

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 ❯

AI Engineer to join our AI engineering team. This role is central to designing, developing, and iterating on fast-paced prototypes that explore the latest in LLMs, autonomous agents, semantic search, and reasoning workflows. The ideal candidate is proficient in Python, experienced in building multi-step intelligent systems, and comfortable working across UI, APIs, cloud AI platforms, and … Autogen. Engineer and tune prompts to enhance the performance and reliability of generative tasks. Design RAG systems using vector databases like Pinecone, Chroma, and PosgreSQL for contextual retrieval. Incorporate semantic search and embedding strategies for more relevant and grounded LLM responses. Utilize Guardrails to implement applications that adhere to responsible AI guidelines. Optimize model performance for latency, throughput More ❯

with agentic AI , multi-agent frameworks, or LLM orchestration Full stack engineering skills (Python/Node.js ) with solid AWS experience Experience with document parsing , unstructured data ingestion, and vector search Understanding of embedding models , RAG pipelines, and semantic search Knowledge of COPE, TIV, deductibles, risk scoring , or insurance use cases is a plus Comfortable working in a More ❯

technology research and development cycle from research and design to implementation and evaluation. A background in areas such as LLM based agents, knowledge graph, knowledge reasoning/inference and semantic search (text/image/video) is desired. Responsibilities as Knowledge Computing Researcher : Design and implement core modules in knowledge-augmented agent systems, including knowledge retrieval, memory modelling … structured and unstructured knowledge from multiple modalities. Architect solutions that deeply couple retrieval systems (RAG, KGs, databases) with agent planning, reasoning, and execution workflows. Work closely with LLM platforms, search infrastructure, and knowledge graph systems to build collaborative end-to-end agent solutions. Translate cutting-edge research into deployable systems across scenarios such as virtual assistants, intelligent QA, multi More ❯

AI engineering team. This role is at the cutting edge of applied LLM development—rapidly prototyping intelligent systems that leverage autonomous agents, reasoning workflows, RAG pipelines, and real-time semantic search. You’ll work across frameworks like LangChain, LangGraph, CrewAI, and LangFlow, designing smart, multi-step agents that can interact with APIs, memory modules, structured databases, and UIs. If … and innovate. As a Generative & Agentic AI Engineer, you will: Build fast, iterative prototypes using LLMs and agent frameworks Design and implement agent workflows, memory handling, RAG systems, and semantic search Integrate vector DBs (Pinecone, FAISS, Chroma), cloud AI services, and APIs Develop lightweight UIs (Streamlit, Gradio, React) and observability for demos Work hands-on with prompt engineering … guardrails, and AI safety tools Requirements: Hands-on experinece working with GCP and Google teams Experience with LangChain, LangGraph, CrewAI, Autogen, or similar frameworks Background in RAG, embeddings, vector search, and memory architecture Familiarity with cloud AI platforms and deploying models via APIs Comfortable building end-to-end prototypes (backend to simple UI) Max 2-month notice period ideally More ❯

would be working as part of a high calibre team of engineers and researchers to build intelligent agent systems powered by large language models, knowledge graphs, and multi-modal semantic search. This is a unique opportunity to apply cutting-edge research to real-world AI systems with meaningful impact across applications such as intelligent assistants, knowledge-based reasoning, and … from multiple modalities (text, image, video) into agent workflows Develop solutions coupling retrieval (KGs, RAG, databases) with planning, reasoning, and execution logic Collaborate with engineering teams on LLM platforms, search infrastructure, and agent systems Translate research into production-ready applications across AI development tools, QA systems, and assistant use-cases Contribute to core algorithm development and support product scaling … ACL, NeurIPS, ICML, EMNLP, ICLR, AAAI) Strong coding and software design skills Experience working across research and applied development in a collaborative environment Keywords: Knowledge Graphs/LLMs/Semantic Search/Knowledge Reasoning/NLP/Agent Systems/RAG/OWL/SPARQL/Transformers/Deep Learning/AI Assistants/QA Systems/Pytorch More ❯

data science, and behavioural modelling to drive meaningful insights and innovations. As AI agents become the norm in this industry, so does the need for efficient legal information retrieval, semantic search capabilities, and structured knowledge representation. Your work will bridge the gap between advanced search technologies and the complex information needs of the legal domain, making legal … engineering legal knowledge base construction specialised embedding methods for multimodal content in the legal domain Develop methods for retrieval and reasoning over legal knowledge bases and systems (e.g. hybrid search approaches combining symbolic and neural techniques, query understanding and rewriting for legal search) Performing fine-tuning and reinforcement learning to teach language models how to interact with new More ❯

working in a fast-paced, agile environment. Excellent communication and collaboration skills. Nice to Have Experience with workflow orchestration tools (e.g., Temporal, Airflow). Familiarity with vector databases or semantic search tools. Experience building internal tooling or developer productivity enhancements using AI. Exposure to customer support AI tools or RAG (retrieval augmented generation) systems. Why Join Paydock? Work More ❯

to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is 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 science, and behavioural modelling to drive meaningful insights and innovations. As AI agents become the norm in this industry, so does the need for efficient legal information retrieval, semantic search capabilities, and structured knowledge representation. Your work will bridge the gap between advanced search technologies and the complex information needs of the legal domain, making legal … engineering Legal knowledge base construction Specialised embedding methods for multimodal content in the legal domain Develop methods for retrieval and reasoning over legal knowledge bases and systems (e.g., hybrid search approaches combining symbolic and neural techniques, query understanding and rewriting for legal search) Perform fine-tuning and reinforcement learning to teach language models how to interact with new More ❯

to play a key role in the development of "Ask Verto," our unique AI-leveraged data research tool. You will be responsible for backend development, including technical solutions for semantic search, data commons, and vector databases. Additionally, you will contribute to the ongoing maintenance and iteration of our products. Responsibilities Investigate and implement technical solutions for semantic search within the tool. Develop the backend for the interactive survey features and vector databases. Ensure efficient data processing and accurate results for natural language queries. Develop functionalities for administrators to review and validate data submitted to the commons. Participate in daily standups and bi-weekly review/planning calls with the client. Provide ongoing backend maintenance and … to AI fine-tuning as needed. Requirements Proven experience with Ruby on Rails development. Strong understanding of backend development, database design, and API creation. Experience with or understanding of semantic search technologies and AI applications is a plus. Ability to work within a ScrumBan methodology. Excellent problem-solving skills and attention to detail. Strong communication and collaboration abilities. More ❯

AI engineering team. This role is at the cutting edge of applied LLM development—rapidly prototyping intelligent systems that leverage autonomous agents, reasoning workflows, RAG pipelines, and real-time semantic search. You’ll work across frameworks like LangChain, LangGraph, CrewAI, and LangFlow, designing smart, multi-step agents that can interact with APIs, memory modules, structured databases, and UIs. If … and innovate. As a Generative & Agentic AI Engineer, you will: Build fast, iterative prototypes using LLMs and agent frameworks Design and implement agent workflows, memory handling, RAG systems, and semantic search Integrate vector DBs (Pinecone, FAISS, Chroma), cloud AI services, and APIs Develop lightweight UIs (Streamlit, Gradio, React) and observability for demos Work hands-on with prompt engineering … tools Requirements: Strong Python development skills Hands-on experinece working with GCP and Google teams Experience with LangChain, LangGraph, CrewAI, Autogen, or similar frameworks Background in RAG, embeddings, vector search, and memory architecture Familiarity with cloud AI platforms and deploying models via APIs Comfortable building end-to-end prototypes (backend to simple UI) Max 2-month notice period ideally More ❯

AI engineering team. This role is at the cutting edge of applied LLM development—rapidly prototyping intelligent systems that leverage autonomous agents, reasoning workflows, RAG pipelines, and real-time semantic search. You’ll work across frameworks like LangChain, LangGraph, CrewAI, and LangFlow, designing smart, multi-step agents that can interact with APIs, memory modules, structured databases, and UIs. If … and innovate. As a Generative & Agentic AI Engineer, you will: Build fast, iterative prototypes using LLMs and agent frameworks Design and implement agent workflows, memory handling, RAG systems, and semantic search Integrate vector DBs (Pinecone, FAISS, Chroma), cloud AI services, and APIs Develop lightweight UIs (Streamlit, Gradio, React) and observability for demos Work hands-on with prompt engineering … tools Requirements: Strong Python development skills Hands-on experinece working with GCP and Google teams Experience with LangChain, LangGraph, CrewAI, Autogen, or similar frameworks Background in RAG, embeddings, vector search, and memory architecture Familiarity with cloud AI platforms and deploying models via APIs Comfortable building end-to-end prototypes (backend to simple UI) Max 2-month notice period ideally 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 ❯

CD, Docker, Kubernetes, and AWS Proven delivery of NLP/OCR projects with unstructured data Experience managing or mentoring engineers Bonus points for: Experience in regulated domains Knowledge of semantic search, graph/vector databases Java or C# background and understanding of SOLID principles 📩 Interested? Message me here or email mmatysik@trg-uk.com More ❯