1 to 25 of 80 Semantic Search Jobs in the UK

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 ❯

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 ❯

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 ❯

Language Models (LLMs) including fine-tuning, prompt engineering, and working daily with models like GPT, Claude, Gemini Hands-on experience with vector databases (e.g., OpenSearch, FAISS) for efficient similarity search and semantic search & retrieval of text embeddings Skilled in implementing conversational AI systems leveraging APIs like OpenAI Chat Completion and Assistant endpoints AWS, Terraform, GitHub Actions (CI More ❯

Azure and Amazon AWS, and especially their AI offerings (Azure OpenAI and Bedrock). Familiarity with Terraform and/or cloud agnostic IaC. Experience with Google Cloud, Vector Databases, Semantic Search and Language Models would be a bonus. About the Department Our department comprises four key teams: AI Engineering, AI Enablement, Responsible AI, and Intelligent Automation, collaborating on 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 ❯

Azure and Amazon AWS, and especially their AI offerings (Azure OpenAI and Bedrock). Familiarity with Terraform and/or cloud agnostic IaC. Experience with Google Cloud, Vector Databases, Semantic Search and Language Models would be a bonus. About the Department Our department comprises four key teams: AI Engineering, AI Enablement, Responsible AI, and Intelligent Automation, collaborating on More ❯

delivery in applied AI. What You'll Be Doing Design and develop AI/ML solutions to enhance investment decision-making and automate analyst workflows. Build tools that improve semantic search, NLP, knowledge extraction, and internal research capabilities. Collaborate with portfolio managers, researchers, and data engineers to translate business problems into ML use cases. Implement, evaluate, and optimize 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 ❯

for someone who wants to be part of a founding team. The Role: Develop and deploy LLM-based solutions tailored to specific business needs (e.g., chatbots, summarization, content generation, semantic search) Fine-tune and customize pre-trained LLMs for targeted applications Conduct prompt engineering, few-shot learning, and to optimise model performance Build pipelines for scalable model training More ❯

for someone who wants to be part of a founding team. The Role: Develop and deploy LLM-based solutions tailored to specific business needs (e.g., chatbots, summarization, content generation, semantic search) Fine-tune and customize pre-trained LLMs for targeted applications Conduct prompt engineering, few-shot learning, and to optimise model performance Build pipelines for scalable model training More ❯

for someone who wants to be part of a founding team. The Role: Develop and deploy LLM-based solutions tailored to specific business needs (e.g., chatbots, summarization, content generation, semantic search) Fine-tune and customize pre-trained LLMs for targeted applications Conduct prompt engineering, few-shot learning, and to optimise model performance Build pipelines for scalable model training 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 ❯

like LLMs, foundation models, vector databases. Defining solution requirements via business analysis. Developing and deploying machine learning models with modern techniques. Integrating models with vector databases and embeddings for semantic search and RAG applications. Working within a Data Mesh architecture, collaborating across domains, and deploying solutions using Docker and Kubernetes. Certifications and Experience Masters-level degree or higher. 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 ❯

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 ❯

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 ❯

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 ❯