1 to 25 of 34 Semantic Search Jobs in England

and high-quality production code, and reviews and debugs code written by others, with a focus on cloud-based systems using AWS and Python. Implements and optimizes RAG-based semantic search and LLM inference workflows using OpenAI and Claude models. Drives decisions that influence the product design, application functionality, and technical operations and processes. Serves as a function … capabilities. Practical cloud-native experience, specifically with AWS. Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field. Preferred qualifications, capabilities, and skills Experience with RAG-based semantic search and LLM inference workflows using OpenAI and Claude models. Proven track record of proposing solutions independently and owning execution end-to-end in an individual contributor role. 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. 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 of AI. What is The Role The Search Inference team is responsible for bringing performant, ergonomic, and cost effective … machine learning (ML) model inference to Search workflows. ML inference has become a crucial part of the modern search experience whether used for query understanding, semantic search, RAG, or any other GenAI use-case. Our goal is to simplify ML inference in Search workflows by focusing on large scale inference capabilities for embeddings and reranking More ❯

techniques (e.g. CatBoost, XGBoost, RoBERTa), and leveraging both structured and unstructured data sources. Experimenting with the integration and fine-tuning of models with Vector databases and embeddings to support semantic search, RAG (retrieval-augmented generation), and domain-specific applications. Working within a Data Mesh architecture, collaborating across domains to ensure scalable, interoperable data products; containerising solutions with Docker More ❯

techniques (e.g. CatBoost, XGBoost, RoBERTa), and leveraging both structured and unstructured data sources. Experimenting with the integration and fine-tuning of models with Vector databases and embeddings to support semantic search, RAG (retrieval-augmented generation), and domain-specific applications. Working within a Data Mesh architecture, collaborating across domains to ensure scalable, interoperable data products; containerising solutions with Docker 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯