76 to 83 of 83 Retrieval-Augmented Generation Jobs in the UK excluding London

Scientist into their AI Research team, focusing on LLMs, RAGs, Agent-based systems and multimodal AI. Responsibilities: Lead the technical design and implementation of sophisticated LLM-based systems, including RAG, agent-based architectures, and multimodal AI solutions. Oversee the lifecycle of LLM projects, from model pre-training and fine-tuning to evaluation and deployment, ensuring alignment with advanced use cases. …/ML Exp. developing, fine-tuning, and deploying LLMs. Solving algo problems from end-to-end Exp. preparing data, then training models on GPUs Proficient in advanced methodologies like RAG and agent systems, keeping up to date with latest tech, papers, and understanding the theory behind advanced models. Expertise in frameworks such as PyTorch, TensorFlow, and Hugging Face. Strong understanding More ❯

Scientist into their AI Research team, focusing on LLMs, RAGs, Agent-based systems and multimodal AI. Responsibilities: Lead the technical design and implementation of sophisticated LLM-based systems, including RAG, agent-based architectures, and multimodal AI solutions. Oversee the lifecycle of LLM projects, from model pre-training and fine-tuning to evaluation and deployment, ensuring alignment with advanced use cases. …/ML Exp. developing, fine-tuning, and deploying LLMs. Solving algo problems from end-to-end Exp. preparing data, then training models on GPUs Proficient in advanced methodologies like RAG and agent systems, keeping up to date with latest tech, papers, and understanding the theory behind advanced models. Expertise in frameworks such as PyTorch, TensorFlow, and Hugging Face. Strong understanding More ❯

Scientist into their AI Research team, focusing on LLMs, RAGs, Agent-based systems and multimodal AI. Responsibilities: Lead the technical design and implementation of sophisticated LLM-based systems, including RAG, agent-based architectures, and multimodal AI solutions. Oversee the lifecycle of LLM projects, from model pre-training and fine-tuning to evaluation and deployment, ensuring alignment with advanced use cases. …/ML Exp. developing, fine-tuning, and deploying LLMs. Solving algo problems from end-to-end Exp. preparing data, then training models on GPUs Proficient in advanced methodologies like RAG and agent systems, keeping up to date with latest tech, papers, and understanding the theory behind advanced models. Expertise in frameworks such as PyTorch, TensorFlow, and Hugging Face. Strong understanding More ❯

hunt for an Technical Architect who will be leading on AI Solutions - this will include: Design, Architect & deploy next-gen GenAI solutions Supercharge natural language interfaces Push boundaries with RAG models, multi-agent systems & more Build robust AI evaluation & monitoring frameworks Mentor, lead & inspire technical team in delivering AI products Experience Required Proven GenAI solution deployment (AWS Bedrock or similar … Deep knowledge of RAG models & agent workflows Experience with GenAIOps, AI security, and responsible AI Leadership skills & a builder's mindset Built and Architected an AI product, and takent to market Interview are happening WC 18/8/25 - this is a 2 stage interview process, to be undertaken remotely. All applicants must have full rights to work in More ❯

Experience working with LLMs and prompt design (ideally OpenAI or similar) An understanding of structured data (SQL, JSON, CSV) and unstructured text (PDFs Exposure to RAG architectures and vector stores (such as FAISS, Pinecone...) Prompt Engineer (AI & Data) – Could suit a Graduate/Junior or Experienced professional Location: Remote (M4/M5/M50 area preferred but flexible) Salary … the join the R&D team and design, test and refine prompts , clean and map unstructured text and structured fields into usable metadata and semantic indexes for use in RAG systems and collaborate with product and design teams to embed LLM-powered assistants into customer facing healthcare support tools. What You'll Do Work across LLM design, structured data integration … Bring Experience working with LLMs and prompt design (ideally OpenAI or similar) An understanding of structured data (SQL, JSON, CSV) and unstructured text (PDFs, documents, form data) Exposure to RAG architectures and vector stores (such as FAISS, Pinecone.....) The ability to work with and communicate with multi-disciplinary teams at all levels of an organization Any experience in a professional More ❯

high-performance services using Golang in secure environments Develop ingestion and processing pipelines for transcription and structured/unstructured data Contribute to intelligent data flows including graph-based and RAG inference pipelines Expose well-structured APIs to support real-time dashboards and NLP workflows Deploy and scale systems using Kubernetes and Docker Collaborate with platform and data science teams to … orchestration tooling (e.g. Argo), and Kafka or equivalent Strong database knowledge (Postgres preferred) Ability to design and scale APIs and backend pipelines for data-rich environments Bonus: Familiarity with RAG pipelines, transcription tooling, vector DBs, or LLM deployment Bonus: Prior experience within Defence, aerospace, or highly regulated industries Why It Stands Out: This isnt a generic software build. Youll help More ❯

high-performance services using Golang in secure environments Develop ingestion and processing pipelines for transcription and structured/unstructured data Contribute to intelligent data flows including graph-based and RAG inference pipelines Expose well-structured APIs to support real-time dashboards and NLP workflows Deploy and scale systems using Kubernetes and Docker Collaborate with platform and data science teams to … orchestration tooling (e.g. Argo), and Kafka or equivalent Strong database knowledge (Postgres preferred) Ability to design and scale APIs and backend pipelines for data-rich environments Bonus: Familiarity with RAG pipelines, transcription tooling, vector DBs, or LLM deployment Bonus: Prior experience within Defence, aerospace, or highly regulated industries Why It Stands Out: This isn’t a generic software build. You More ❯

support secure, air-gapped AI deployments, with a focus on NLP-based tooling Develop pipelines for transcription ingestion and real-time analytical insight generation Support graph and RAG-based inference layers using data from structured and unstructured sources Build and expose APIs for frontend consumption, enabling natural-language querying, dynam click apply for full job details More ❯