1 to 25 of 115 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 ❯

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 ❯

agents, knowledge graphs and chatbots to enhance user experience and efficiency. Leading projects that utilize Retrieval-Augmented Generation (RAG) and GraphRAG techniques. Developing and optimizing AI models using machine learning and AI engineering platforms. Mentoring and guiding team members to foster a culture of … showcasing these solutions to clients and communicating their business impact. Experience in providing solutions using Retrieval-Augmented Generation (RAG), GraphRAG, knowledge graphs, code agents, deep research agents, and chatbots. Familiarity with AI engineering platforms (Azure AI Foundry, AWS Bedrock, GCP Vertex AI) and employee More ❯

About Quantum: Quantum is building next-generation AI and trading technologies that harness cutting-edge research and data science. As part of our rapid growth, we are seeking a highly skilled Senior Data Engineer to support our Data & AI team by designing and maintaining robust, scalable, and production … quality, developing validation frameworks, and contributing to continuous data improvement initiatives. Collaboration with AI Teams: Work closely with the Principal Data Scientist to operationalise RAG systems, fine-tune data retrieval processes, and optimise training datasets for AI model development. Automation and Optimisation: Automate ETL (Extract, Transform, Load) processes … Dask. Familiarity with MLOps and deploying AI/ML models into production environments. Knowledge of Retrieval-Augmented Generation (RAG) frameworks or interest in learning and supporting RAG systems. Experience implementing scalable APIs and integrating data services with AI and analytics platforms. Strong understanding of More ❯

About Quantum: Quantum is building next-generation AI and trading technologies that harness cutting-edge research and data science. As part of our rapid growth, we are seeking a highly skilled Senior Data Engineer to support our Data & AI team by designing and maintaining robust, scalable, and production … quality, developing validation frameworks, and contributing to continuous data improvement initiatives. Collaboration with AI Teams: Work closely with the Principal Data Scientist to operationalise RAG systems, fine-tune data retrieval processes, and optimise training datasets for AI model development. Automation and Optimisation: Automate ETL (Extract, Transform, Load) processes … Dask. Familiarity with MLOps and deploying AI/ML models into production environments. Knowledge of Retrieval-Augmented Generation (RAG) frameworks or interest in learning and supporting RAG systems. Experience implementing scalable APIs and integrating data services with AI and analytics platforms. Strong understanding of More ❯

to redefine primary care while helping people live happier, healthier, and longer. Education Masters Degree About the Role You will design, build, and optimize RAG pipelines that combine large language models (LLMs) with domain-specific retrieval systems, enabling natural language understanding and reasoning over patient data, clinical guidelines … work will directly impact how patients and clinicians interact with our platform, enabling safe, accurate, and context-aware content surfacing. Responsibilities Design and implement RAG architectures using open-source and potentially proprietary LLMs (e.g., LLaMA, Mistral, OpenAI, Anthropic). Build and maintain retrieval pipelines over structured and unstructured … notes, device logs, clinical documentation). Develop indexing strategies using vector databases (e.g., FAISS, Weaviate, Pinecone) and embedding models (e.g., BioBERT, ClinicalBERT). Integrate RAG outputs into user-facing applications, ensuring responses are grounded, reliable, and privacy-compliant. Work closely with product, clinical, and data science teams to fine-tune More ❯

agents to interact autonomously with data sources and external APIs using advanced prompt engineering and retrieval-augmented generation (RAG) Fine-tune and optimize pre-trained large language models and multi-modal models for targeted use cases, ensuring high performance and low latency in production. More ❯

AI initiatives span categorization, summarization, data analysis, automated content generation, and rich media analysis -leveraging both existing AI/ML tools (LLMs, RAG, embeddings, agentic workflows) and custom solutions. You'll collaborate across teams to build practical, scalable AI solutions - where precision matters. With a "you build it … Select, train, and fine-tune AI models based on need, leveraging appropriate techniques (e.g. LLMs, Retrieval-Augmented Generation (RAG), Vector Databases, Embeddings, Multi-modal AI, Agentic Workflows) (Model Development). Integrate and deploy scalable AI based applications, backend services and APIs (Deployment). Develop More ❯

AI agents, leveraging LLMs, reinforcement learning, vector databases, and autonomous systems . As a key AI strategy leader , you'll define the next-generation consumer experiences , enabling real-time merchant insights , AI-powered Ops automation , and cutting-edge chatbot capabilities . You will collaborate closely with executive leadership … making, and task execution. LLM Fine-Tuning & Enhancement: Adapt foundational models like GPT, Llama, integrating retrieval-augmented generation (RAG), personalization, and continuous improvement loops. Multi-Agent Systems: Implement collaborative AI systems that solve complex challenges in payments and customer interactions. Long-Term AI Memory … Learning, or related field. Experience: 7+ years in AI/ML development, with expertise in Python, TensorFlow, and PyTorch. Core AI Knowledge: LLM Optimization (RAG, fine-tuning, prompt engineering) Vector databases for AI retrieval Multi-agent systems and reinforcement learning Cloud AI deployment (AWS, Azure), inference optimization A More ❯

tune SLMs/LLMs using domain-specific data (e.g., ITSM, security, operations) • Design and optimize Retrieval-Augmented Generation (RAG) pipelines with vector DBs (e.g., FAISS, Chroma, Weaviate, Pinecone) • Develop agent-based architectures using LangGraph, AutoGen, CrewAI, or custom frameworks • Integrate AI agents with enterprise 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 ❯

NLP), Generative AI, Multimodal Large Language Model (MLLM), Natural Language Understanding (NLU), Machine Learning (ML), Retrieval-Augmented Generation (RAG), Computer Vision, Responsible AI, LLM Agents, Evaluation, and Model Adaptation. Key job responsibilities As an Applied Scientist on our team, you will be responsible for … test experiments, optimize and deploy your models into production, working closely with software engineers. - Establish automated processes for large-scale data analysis and generation, machine-learning model development, model validation and serving. - Communicate results and insights to both technical and non-technical audiences, including through presentations and written More ❯

systems for high-speed, accurate search functionality. • Explore and implement advanced techniques, such as Retrieval-Augmented Generation (RAG), to enhance AI capabilities. • Conduct experiments to measure and improve the performance of NLP models. • Build custom language models tailored to specific industry requirements. What 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 ❯

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 ❯

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 ❯

insight, integrity, and a passion for making things better. Role Overview We are looking for a Data Scientist with experience in RAG (Retrieval-Augmented Generation) , Agentic AI frameworks , and deep domain understanding of Finance/Savings platforms . This hybrid role (UK-based) is … ideal candidate thrives in complex environments and bridges the gap between data, automation, and user experience. Key Responsibilities AI-Driven Architecture: Design and implement RAG pipelines that enhance platform intelligence and content retrieval Agentic AI Integration: Develop and fine-tune autonomous agents for workflow automation, intelligent decisioning, and … Science, AI, Computer Science, or related quantitative field Experience: 5+ years in data science roles with platform/product experience 2+ years working on RAG implementations using tools like LangChain, LlamaIndex, or custom vector stores Experience building or deploying Agentic AI architectures (e.g., AutoGPT, CrewAI, OpenAgents) Strong grasp of CRM More ❯

insight, integrity, and a passion for making things better. Role Overview We are looking for a Data Scientist with experience in RAG (Retrieval-Augmented Generation) , Agentic AI frameworks , and deep domain understanding of Finance/Savings platforms . This hybrid role (UK-based) is … ideal candidate thrives in complex environments and bridges the gap between data, automation, and user experience. Key Responsibilities AI-Driven Architecture: Design and implement RAG pipelines that enhance platform intelligence and content retrieval Agentic AI Integration: Develop and fine-tune autonomous agents for workflow automation, intelligent decisioning, and … Science, AI, Computer Science, or related quantitative field Experience: 5+ years in data science roles with platform/product experience 2+ years working on RAG implementations using tools like LangChain, LlamaIndex, or custom vector stores Experience building or deploying Agentic AI architectures (e.g., AutoGPT, CrewAI, OpenAgents) Strong grasp of CRM More ❯

insight, integrity, and a passion for making things better. Role Overview We are looking for a Data Scientist with experience in RAG (Retrieval-Augmented Generation) , Agentic AI frameworks , and deep domain understanding of Finance/Savings platforms . This hybrid role (UK-based) is … ideal candidate thrives in complex environments and bridges the gap between data, automation, and user experience. Key Responsibilities AI-Driven Architecture: Design and implement RAG pipelines that enhance platform intelligence and content retrieval Agentic AI Integration: Develop and fine-tune autonomous agents for workflow automation, intelligent decisioning, and … Science, AI, Computer Science, or related quantitative field Experience: 5+ years in data science roles with platform/product experience 2+ years working on RAG implementations using tools like LangChain, LlamaIndex, or custom vector stores Experience building or deploying Agentic AI architectures (e.g., AutoGPT, CrewAI, OpenAgents) Strong grasp of CRM More ❯

the forefront of tech, working with advanced AI models, including large language models (LLMs) and Retrieval-Augmented Generation (RAG) techniques, gaining hands-on experience with the latest innovations. High-impact role: Your contributions will directly shape BRYTER's growth and success. Collaborative and innovative 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 ❯