1 to 25 of 85 Semantic Search Jobs in England

LLM's for Retrieval Augmented Generation (RAG) architecture including opensource. Experience with LLM architecture (e.g., Transformer, GANs, VAEs), Fine-tuning PEFT/LoRA, Context embedding, Vector database technologies and Semantic Search techniques & tools. Proficiency in programming languages such as Python and experience with NLP libraries such as NLTK, spaCy, Transformers, Hugging Face, BERT and Gen AI frameworks like 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 ❯

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 ❯

functional teams to implement machine learning solutions for diverse applications, including but not limited to text embeddings, sentiment analysis, question answering, summarization, and topic modeling. Utilize your expertise in semantic search, prompt engineering, and large language models (LLMs) to create robust NLP systems. Optimise and fine-tune models for production environments and handle real-world challenges related to … text embeddings, named entity recognition, machine translation, summarization, sentiment analysis, and more. Hands-on experience with pre-trained LLMs such as BERT and GPT, and advanced NLP techniques like semantic search, RAG, and agent-based models. Professional Experience : Commercial experience in NLP-focused roles. Our heavy involvement in educational NLP research with real world applications. Proven track record 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 ❯

learning tasks. Build and deploy AI applications leveraging: Retrieval Augmented Generation (RAG) LangChain and Prompt Engineering LLMs (OpenAI, Huggingface Transformers) Vector Databases (FAISS, Pinecone, Milvus) Develop robust pipelines for semantic search and retrieval chains in real-world production systems. Write clean, efficient, modular, and production-grade Python code. Collaborate closely with cross-functional teams including Data Engineering, DevOps … XGBoost, SVM, Random Forests, Logistic Regression Deep learning models: CNNs, RNNs, Transformers (BERT, GPT) Unsupervised learning: K-Means, PCA Experience with: RAG architecture, LangChain, and advanced prompt engineering Vector search techniques (BM25, Dense Passage Retrieval) Python libraries: scikit-learn, TensorFlow, PyTorch, Huggingface Transformers Proficiency in working with cloud environments: AWS, Azure, or GCP Nice To Have Front-end development 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 ❯

Data Scientist (Semantic Search/Recommender Systems) Join to apply for the Data Scientist (Semantic Search/Recommender Systems) role at Tesco Technology . Get AI-powered advice on this job and more exclusive features. As a Data Scientist within Semantic Search, you will influence the search experience on the Tesco website by … the systems architecture, Machine Learning components, and associated technologies. Using data to train and fine-tune models. Developing efficient and high-quality code in Software Engineering. Collaborating closely with Search Engineers, ML Engineers, and Data Scientists. Promoting data science internally and effectively communicating sophisticated solutions to non-technical colleagues. Requirements To excel in this role, we seek individuals with … a strong blend of Machine Learning and Software Engineering skills. Key requirements include: Experience as a Data Scientist or a PhD graduate with expertise in Semantic Search, recommender systems, information retrieval, or LLMs. PhD in Mathematics, Engineering, Computer Science, or a related field. Hands-on experience with Deep Learning approaches, including modern language models based on transformer architecture. 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 ❯

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 ❯

Scientist/Associate – Upstream Process Development Harrow, England, United Kingdom 1 week ago Luton, England, United Kingdom 5 days ago Hertfordshire, England, United Kingdom 3 weeks ago Data Scientist (Semantic Search/Recommender Systems) Research Scientist/Commercial Experience London, England, United Kingdom 2 days ago Research Scientist/Commercial Experience London, England, United Kingdom 2 months ago … Data Scientist (Semantic Search/Recommender Systems) Harrow, England, United Kingdom 3 days ago Luton, England, United Kingdom 2 days ago High Wycombe, England, United Kingdom 2 weeks ago Tottenham, England, United Kingdom 2 weeks ago Hoddesdon, England, United Kingdom 2 weeks ago Research Assistant/Associate in Cognitive Robotics Milton Keynes, England, United Kingdom 3 weeks ago More ❯

Social network you want to login/join with: ? Python, PostgreSQL, LLMs, RAG, Semantic Search, Knowledge Representation, Fine-tuning ? Central London | 4-days on-site ? Seed-funded. Aiming for Series A in 2025 We’re working with an exciting AI Ed-tech start-up in London that’s transforming the educational experience. Fresh from securing Seed funding and More ❯

Social network you want to login/join with: ? Python, PostgreSQL, LLMs, RAG, Semantic Search, Knowledge Representation, Fine-tuning ? Central London | 4-days on-site ? Seed-funded. Aiming for Series A in 2025 We’re working with an exciting AI Ed-tech start-up in London that’s transforming the educational experience. Fresh from securing Seed funding and 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 ❯