1 to 25 of 83 Permanent Retrieval-Augmented Generation Jobs in London

interactions. The role will focus on projects to leverage state-of-the-art generative AI, retrieval-augmented generation (RAG), and reasoning frameworks to build intelligent and context-aware systems. We are seeking talented Machine Learning Engineers with full-stack software development experience to join … relevancy engineering. Conversational AI Development : Design, train, fine-tune, and deploy LLMs with reasoning capabilities. Retrieval-Augmented Generation (RAG): Implement, optimise, and scale RAG pipelines for effective information retrieval from structured and unstructured sources. Model Fine-Tuning & Training : Train domain-specific models … skills & experience: 3-5+ years in machine learning and software development Proficient in Python, PyTorch or TensorFlow or Hugging Face Transformers Experience with RAG, LLM fine-tuning, and expertise in AWS and cloud-native AI deployments. Full-stack experience (React, TypeScript, Node.js) and API development. Familiarity with vector search More ❯

building and optimizing Large Language Model (LLM) inferences and creating robust web services. This includes developing event-driven and request-response systems to run RAG (Retrieval-Augmented Generation) answer generation pipelines, essential for delivering sophisticated AI-driven solutions. Your role will require … an understanding of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code More ❯

building and optimizing Large Language Model (LLM) inferences and creating robust web services. This includes developing event-driven and request-response systems to run RAG (Retrieval-Augmented Generation) answer generation pipelines, essential for delivering sophisticated AI-driven solutions. Your role will require … an understanding of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code More ❯

building and optimizing Large Language Model (LLM) inferences and creating robust web services. This includes developing event-driven and request-response systems to run RAG (Retrieval-Augmented Generation) answer generation pipelines, essential for delivering sophisticated AI-driven solutions. Your role will require … an understanding of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code More ❯

Models (LLMs) to real-world challenges like email triage, document parsing, and data enrichment. Implement retrieval-augmented generation (RAG) to power internal AI assistants with trusted business knowledge. Rapidly prototype and iterate on Proofs of Concept to test ideas and gather user feedback early. … and vector databases. Familiarity with automation platforms like n8n, Zapier, or similar. Solid understanding of retrieval-augmented generation (RAG) methods. Strong problem-solving skills and the ability to design practical AI solutions with business outcomes in mind. Excellent communication skills – able to work cross More ❯

Models (LLMs) to real-world challenges like email triage, document parsing, and data enrichment. Implement retrieval-augmented generation (RAG) to power internal AI assistants with trusted business knowledge. Rapidly prototype and iterate on Proofs of Concept to test ideas and gather user feedback early. … and vector databases. Familiarity with automation platforms like n8n, Zapier, or similar. Solid understanding of retrieval-augmented generation (RAG) methods. Strong problem-solving skills and the ability to design practical AI solutions with business outcomes in mind. Excellent communication skills – able to work cross More ❯

Models (LLMs) to real-world challenges like email triage, document parsing, and data enrichment. Implement retrieval-augmented generation (RAG) to power internal AI assistants with trusted business knowledge. Rapidly prototype and iterate on Proofs of Concept to test ideas and gather user feedback early. … and vector databases. Familiarity with automation platforms like n8n, Zapier, or similar. Solid understanding of retrieval-augmented generation (RAG) methods. Strong problem-solving skills and the ability to design practical AI solutions with business outcomes in mind. Excellent communication skills – able to work cross More ❯

GPT-4, Claude, Gemini, and beyond) Knowledgeable of the latest developments in diffusion models and other generative frameworks for both text and image generation Competent in Generative AI and language models to spearhead innovative initiatives that leverage cutting-edge techniques in NLP and AI Adept at applying advanced … and deployment in production Choose relevant computational tools for study, experiment, or trial research objectives Drive the development of innovative solutions for language generation, text synthesis, and creative content generation using the latest state … of-the-art techniques Develop and implement advanced Generative AI solutions such as intelligent assistants, Retrieval-Augmented Generation (RAG) systems, and other innovative applications Produce clear, concise, well-organized, and error-free computer programs with the appropriate technological stack Present results directly to stakeholders More ❯

GPT-4, Claude, Gemini, and beyond) Knowledgeable of the latest developments in diffusion models and other generative frameworks for both text and image generation Competent in Generative AI and language models to spearhead innovative initiatives that leverage cutting-edge techniques in NLP and AI Adept at applying advanced … and deployment in production Choose relevant computational tools for study, experiment, or trial research objectives Drive the development of innovative solutions for language generation, text synthesis, and creative content generation using the latest state … of-the-art techniques Develop and implement advanced Generative AI solutions such as intelligent assistants, Retrieval-Augmented Generation (RAG) systems, and other innovative applications Produce clear, concise, well-organized, and error-free computer programs with the appropriate technological stack Present results directly to stakeholders More ❯

GPT-4, Claude, Gemini, and beyond) Knowledgeable of the latest developments in diffusion models and other generative frameworks for both text and image generation Competent in Generative AI and language models to spearhead innovative initiatives that leverage cutting-edge techniques in NLP and AI Adept at applying advanced … and deployment in production Choose relevant computational tools for study, experiment, or trial research objectives Drive the development of innovative solutions for language generation, text synthesis, and creative content generation using the latest state … of-the-art techniques Develop and implement advanced Generative AI solutions such as intelligent assistants, Retrieval-Augmented Generation (RAG) systems, and other innovative applications Produce clear, concise, well-organized, and error-free computer programs with the appropriate technological stack Present results directly to stakeholders More ❯

into crafting and optimizing sophisticated AI pipelines. This involves extensive prompt engineering, building and refining Retrieval-Augmented Generation (RAG) systems, and developing agentic AI workflows that deliver powerful analytical capabilities to our users. Master the Domain: Immerse yourself in the world of financial analysis. … You have demonstrable experience building and shipping meaningful projects (at work or independently) using modern AI tools and techniques (e.g., OpenAI, Anthropic, Gemini APIs; RAG, agent frameworks, prompt engineering). Showcasing this via a portfolio, open-source contributions (e.g., a GitHub repo), or detailed project walkthroughs is highly encouraged. Tinkerer More ❯

into crafting and optimizing sophisticated AI pipelines. This involves extensive prompt engineering, building and refining Retrieval-Augmented Generation (RAG) systems, and developing agentic AI workflows that deliver powerful analytical capabilities to our users. Master the Domain: Immerse yourself in the world of financial analysis. … You have demonstrable experience building and shipping meaningful projects (at work or independently) using modern AI tools and techniques (e.g., OpenAI, Anthropic, Gemini APIs; RAG, agent frameworks, prompt engineering). Showcasing this via a portfolio, open-source contributions (e.g., a GitHub repo), or detailed project walkthroughs is highly encouraged. Tinkerer More ❯

working with open-source LLMs (e.g., LLaMA, Mistral, DeepSeek, Qwen, etc.) Experience building and evaluating Retrieval-Augmented Generation (RAG) pipelines, including embedding models and vector search Familiarity with libraries such as Hugging Face Transformers for model development and integration Experience processing and extracting information More ❯

working with open-source LLMs (e.g., LLaMA, Mistral, DeepSeek, Qwen, etc.) Experience building and evaluating Retrieval-Augmented Generation (RAG) pipelines, including embedding models and vector search Familiarity with libraries such as Hugging Face Transformers for model development and integration Experience processing and extracting information More ❯

Engineer with full-stack development experience to work on cutting-edge projects involving Generative AI , Retrieval-Augmented Generation (RAG) , and multi-agent reasoning frameworks . This is a hands-on, end-to-end engineering role with impact across the full ML lifecycle – from experimentation … to deployment. Conversational AI & Reasoning: Design, fine-tune, and deploy advanced LLMs with agentic capabilities RAG Pipelines: Build and optimise scalable pipelines for structured and unstructured data retrieval LLM Training & Fine-Tuning: Use methods like LoRA, QLoRA, SFT, PEFT, and RLHF Inference & Acceleration: Serve models using vLLM, DeepSpeed … 5+ years of experience in ML engineering and software development Deep Python proficiency, with PyTorch, TensorFlow or Hugging Face Proven experience with LLMs, RAG, and deploying cloud-native AI on AWS Strong full-stack skills (React, TypeScript, Node.js) and API development Familiarity with vector databases and multi-agent frameworks Apply More ❯

to solve complex business problems using technologies like Python, Pandas, NumPy, LLMs (OpenAI, open-source), Retrieval-Augmented Generation (RAG) , and modern data stacks. What we're looking for Strong software/data engineering skills (Python, SQL, microservices) Hands-on experience with LLMs, RAG, and More ❯

Hands-on Experience with LLMs : Practical knowledge of working with large language models (LLMs) and retrieval-augmented generation (RAG). Advanced Evaluation Techniques : Expertise in A/B testing, human-in-the-loop evaluation, and GenAI quality metrics, ensuring the quality, relevance, and user More ❯

Hands-on Experience with LLMs : Practical knowledge of working with large language models (LLMs) and retrieval-augmented generation (RAG). Advanced Evaluation Techniques : Expertise in A/B testing, human-in-the-loop evaluation, and GenAI quality metrics, ensuring the quality, relevance, and user More ❯

build and evolve Generative AI (GenAI) proof-of-concepts (POCs) for clients using techniques like Retrieval-Augmented Generation (RAG) and intelligent agents. Support the transition of these POCs into scalable, production-ready solutions. C Contribute to the design and development of full-stack applications More ❯

build and evolve Generative AI (GenAI) proof-of-concepts (POCs) for clients using techniques like Retrieval-Augmented Generation (RAG) and intelligent agents. Support the transition of these POCs into scalable, production-ready solutions. C Contribute to the design and development of full-stack applications More ❯

build and evolve Generative AI (GenAI) proof-of-concepts (POCs) for clients using techniques like Retrieval-Augmented Generation (RAG) and intelligent agents. Support the transition of these POCs into scalable, production-ready solutions. C Contribute to the design and development of full-stack applications More ❯

platform app delivers vetted, evidence‐based answers to frontline clinicians in seconds. We combine large‐language models with rigorous retrieval‐augmented generation (RAG) pipelines so doctors can safely consult clinical guidelines at the bedside. You’ll join a small, product‐obsessed team that ships … evaluate ranking quality, and productionise LLM workflows on Google Cloud. What you’ll do Design & build backend micro‐services (Python/FastAPI) that power RAG pipelines, user queries, and analytics. Develop retrieval infrastructure : orchestrate embedding generation, vector databases (PGVector, Pinecone, Weaviate), and hybrid search. Implement evaluation More ❯

platform app delivers vetted, evidence‐based answers to frontline clinicians in seconds. We combine large‐language models with rigorous retrieval‐augmented generation (RAG) pipelines so doctors can safely consult clinical guidelines at the bedside. You’ll join a small, product‐obsessed team that ships … evaluate ranking quality, and productionise LLM workflows on Google Cloud. What you’ll do Design & build backend micro‐services (Python/FastAPI) that power RAG pipelines, user queries, and analytics. Develop retrieval infrastructure : orchestrate embedding generation, vector databases (PGVector, Pinecone, Weaviate), and hybrid search. Implement evaluation More ❯

world environments Strong Python skills and experience with key ML libraries (e.g., scikit-learn, XGBoost, PyTorch) Exposure to Generative AI technologies (e.g., LLMs, embeddings, RAG systems) Excellent communication skills and ability to engage senior stakeholders Nice to Have: Experience in consulting or client-facing delivery roles Knowledge of cloud platforms More ❯

world environments Strong Python skills and experience with key ML libraries (e.g., scikit-learn, XGBoost, PyTorch) Exposure to Generative AI technologies (e.g., LLMs, embeddings, RAG systems) Excellent communication skills and ability to engage senior stakeholders Nice to Have: Experience in consulting or client-facing delivery roles Knowledge of cloud platforms More ❯