21 of 21 Semantic Search Jobs in London

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale - unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of … search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data - securing and protecting private information more effectively - Elastic's complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise … initiative to improve both themselves and the team through continuous learning and questioning the status quo. What You Will Be Doing: Architect next-generation search solutions: Design and implement cutting-edge solutions utilizing Elastic's latest advancements in AI, semantic search, and vector search, including RAG More ❯

seamlessly combine retrieval-based knowledge and generative text generation to implement and optimize RAG models using first-party and OSS models. Experience with implementing search concepts, such as indexing, scoring, relevancy, faceting, and query rewriting and expansion. Experience with semantic search frameworks and tools/databases such … as LangChain, Faiss, and Pinecone. Understanding of nearest neighbor search concepts. About the Job: As a Generative AI Field Solutions Architect, you will support Google Cloud Sales and Engineering teams to incubate, pilot, and deploy Google Cloud's AI/ML and Generative AI technology with AI native customers More ❯

data retrieval and generation. Develop APIs and microservices and dbt to integrate RAG capabilities with existing data sources (mainly user behaviour data, metadata and semantic layer, stored in Redshift, but also other sources e.g. HR systems, legal repositories, SharePoint, etc.). Manage and optimize LibreChat UI and Openweb UI … Pipelines for chatbot interactions. Data Engineering & Integration: Build efficient data pipelines to support LLM-based querying, semantic search, and metadata retrieval. Integrate structured (SQL-based) and unstructured (documents, reports) data sources for real-time and batch processing. Maintain and troubleshoot Airflow pipelines for embedding extraction and document processing. … Ensure data governance, security, and compliance across all applications. Manage Vector Database (PGVector), including indexing and similarity search optimizations. Application Development: Develop interactive UI components to enable self-serve data access and visualization using React or other web frameworks. Apps examples: generic text to SQL, funnels, user journeys exploration More ❯

D stakeholders and Onyx leadership to develop a strategic roadmap for all customer-facing aspects of Onyx, including data assets, ontology, Knowledge Graph/semantic search, data/computing/analysis platforms, and workbenches. We are seeking a skilled and experienced Senior Product Manager for our Data Platform More ❯

in a cloud-native Azure environment. Role Overview Develop and optimise RAG pipelines using LangChain, LlamaIndex, or Haystack. Build ingestion workflows (OCR, chunking, embedding, semantic search) and integrate with vector databases (FAISS, Pinecone, Qdrant). Ensure seamless integration of GenAI services into business workflows, prioritising security, scalability, and … functional teams (data scientists, architects, engineers) to drive high-performance, enterprise-ready solutions. Key Skills Required Expertise in LLM pipelines, embedding models, and vector search architecture. Strong hands-on experience with the Azure AI stack (Azure OpenAI, Azure Search). Proficient in Python, CI/CD, and MLOps More ❯

in a cloud-native Azure environment. Role Overview Develop and optimise RAG pipelines using LangChain, LlamaIndex, or Haystack. Build ingestion workflows (OCR, chunking, embedding, semantic search) and integrate with vector databases (FAISS, Pinecone, Qdrant). Ensure seamless integration of GenAI services into business workflows, prioritising security, scalability, and … functional teams (data scientists, architects, engineers) to drive high-performance, enterprise-ready solutions. Key Skills Required Expertise in LLM pipelines, embedding models, and vector search architecture. Strong hands-on experience with the Azure AI stack (Azure OpenAI, Azure Search). Proficient in Python, CI/CD, and MLOps More ❯

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 … 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 More ❯

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale - unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of … search and the intelligence of AI to enable everyone to accelerate the results that matter. Role & Responsibilities: Acting as a strategic technical leader in the field - you are a self starter. You lead the lifecycle of agreements from business case, planning and governance, technical architecture, solution build, business modeling …/or cloud/infrastructure technologies. 5+ years of experience working with multinational customers in support of technology sales. An understanding of AI and semantic search and vector technologies, with a focus on RAG, vector search, and NLP. Professional experience architecting/operating solutions built on AWS More ❯

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. More ❯

D stakeholders and Onyx leadership to develop a strategic roadmap for all customer-facing aspects of Onyx, including data assets, ontology, Knowledge Graph/semantic search, data/computing/analysis platforms, and data-powered applications. We are seeking a highly skilled and experienced Senior Product Manager, AIML More ❯

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. More ❯

role, you will: Own the development and application of LLM-based features end-to-end. Build and maintain evaluation frameworks for prompt iteration and semantic retrieval. Optimize embeddings and vector stores for performance and scalability. Interact with users to understand their problems and design solutions. Stay up-to-date … engineering experience at tech and product-driven companies. Experience shipping LLM-based solutions to production. Experience with inference and evaluation platforms. Experience with RAG, semantic search, vector stores, embeddings. Experience building features end-to-end with TypeScript, React.js, and Node.js. Ability to thrive in a fast-paced startup More ❯

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. More ❯

travel industry is a significant advantage. Your hands-on experience with advanced LLM features such as Function Calling and API integrations, Vector Embeddings and semantic search, Prompt Engineering and prompt optimization or RAG (Retrieval-Augmented Generation). Demonstrated experience in cloud-native environments and proficiency in diverse architectural More ❯

travel industry is a significant advantage. Your hands-on experience with advanced LLM features such as Function Calling and API integrations, Vector Embeddings and semantic search, Prompt Engineering and prompt optimization or RAG (Retrieval-Augmented Generation). Demonstrated experience in cloud-native environments and proficiency in diverse architectural More ❯

travel industry is a significant advantage. Your hands-on experience with advanced LLM features such as Function Calling and API integrations, Vector Embeddings and semantic search, Prompt Engineering and prompt optimization or RAG (Retrieval-Augmented Generation). Demonstrated experience in cloud-native environments and proficiency in diverse architectural More ❯

travel industry is a significant advantage. Your hands-on experience with advanced LLM features such as Function Calling and API integrations, Vector Embeddings and semantic search, Prompt Engineering and prompt optimization or RAG (Retrieval-Augmented Generation). Demonstrated experience in cloud-native environments and proficiency in diverse architectural More ❯

travel industry is a significant advantage. Your hands-on experience with advanced LLM features such as Function Calling and API integrations, Vector Embeddings and semantic search, Prompt Engineering and prompt optimization or RAG (Retrieval-Augmented Generation). Demonstrated experience in cloud-native environments and proficiency in diverse architectural More ❯

travel industry is a significant advantage. Your hands-on experience with advanced LLM features such as Function Calling and API integrations, Vector Embeddings and semantic search, Prompt Engineering and prompt optimization or RAG (Retrieval-Augmented Generation). Demonstrated experience in cloud-native environments and proficiency in diverse architectural More ❯

travel industry is a significant advantage. Your hands-on experience with advanced LLM features such as Function Calling and API integrations, Vector Embeddings and semantic search, Prompt Engineering and prompt optimization or RAG (Retrieval-Augmented Generation). Demonstrated experience in cloud-native environments and proficiency in diverse architectural More ❯

travel industry is a significant advantage. Your hands-on experience with advanced LLM features such as Function Calling and API integrations, Vector Embeddings and semantic search, Prompt Engineering and prompt optimization or RAG (Retrieval-Augmented Generation). Demonstrated experience in cloud-native environments and proficiency in diverse architectural More ❯