26 to 50 of 135 Retrieval-Augmented Generation Jobs in the UK

AI-powered solutions. Maintain productive relationships with clinical teams, data scientists, and infrastructure teams to ensure successful deployment of NLP products - including LLM systems, RAG pipelines, and autonomous clinical agents. Provide detailed performance metrics and analysis of NLP systems, including model accuracy, latency, and clinical impact metrics to the Head More ❯

Natural Language Processing and Generative AI to join our AI Experiences team. Our teams are working on exciting initiatives such as: Building and deploying RAG systems, curating data for model training and evaluation, building evaluation systems that facilitate rapid iteration, and understanding how users interact with our systems to identify More ❯

Natural Language Processing and Generative AI to join our AI Experiences team. Our teams are working on exciting initiatives such as: Building and deploying RAG systems, curating data for model training and evaluation, building evaluation systems that facilitate rapid iteration, and understanding how users interact with our systems to identify More ❯

Ideally AWS) Strong Python & SQL experience Experience in advertising, marketing or YouTube/social media video (Highly Desirable) Experience or understanding of LLMS, LangChain, & RAG (Beneficial) Sound of interest? Apply today for immediate consideration! Please note: All candidates must be UK based and have the full right to work in More ❯

Ideally AWS) Strong Python & SQL experience Experience in advertising, marketing or YouTube/social media video (Highly Desirable) Experience or understanding of LLMS, LangChain, & RAG (Beneficial) Sound of interest? Apply today for immediate consideration! Please note: All candidates must be UK based and have the full right to work in More ❯

Strong understanding of machine learning algorithms, NLP, and LLMs with demonstrated business application expertise Experience developing AI-powered automation systems, intelligent assistants/copilots, RAG systems, voice interfaces, and computer vision applications (image and video processing) for enterprise environments Knowledge of advanced AI agent frameworks and architectures such as ReAct More ❯

Alexa+. We work on recent advances in LLM science including automated prompt optimisation, supervised fine tuning, reinforcement learning, model distillation, retrieval augmented generation, model & prompt interpretability and LLM driven data generation. The techniques are used to tune a foundational model to align with Alexa More ❯

needed Our client is an international company that requires a senior Data Scientist with experience in Azure Databricks, Knowledge Graph, Neo4J Graph Database, and RAG pipelines for LLM to join the team. Job Description: Responsibilities: Develop and implement data models and algorithms to solve complex business problems. Utilize Databricks to More ❯

Instruction Tuning, Reinforcement Learning Alignment, Distributed Training, Efficient ML techniques) Post-training techniques for planning & reasoning (e.g. LLMs & Knowledge Graphs, Advanced Prompting, CoT pipelines, RAG, Tool use, etc.) Data-centric Machine Learning (Synthetic Data, Curriculum Learning, learned data-mixtures) Evaluation (Benchmarks, Human-in-the-loop, red teaming/Adversarial Testing More ❯

analytical reasoning. Exceptional communication and collaboration skills. Experience with ML frameworks such as TensorFlow, PyTorch, TensorRT, or ONNX. Experience with Large Language Models, including RAG and fine-tuning techniques. Familiarity with compute infrastructure necessary to support operating AI and ML technology. More ❯

scalable GenAI pipelines that generate high-quality content, from product descriptions, reviews, titles, and other product content. Design and evaluate prompt tuning strategies and RAG systems to ensure factual and engaging outputs. Fine-tune foundation models and develop domain-specific adapters using techniques like LoRA, PEFT, and instruction tuning. Define More ❯

scalable GenAI pipelines that generate high-quality content, from product descriptions, reviews, titles, and other product content. Design and evaluate prompt tuning strategies and RAG systems to ensure factual and engaging outputs. Fine-tune foundation models and develop domain-specific adapters using techniques like LoRA, PEFT, and instruction tuning. Define More ❯

Weights & Biases. A solid background in software engineering and DevOps practices, MLOps deployment, and infrastructure. A knack for generative AI frameworks and SDKs, like RAG, Langchain/LangGraph, Semantic Kernel, and tools such as MS tooling, Co-Pilot Studio, ML Studio, Prompt flow, Kedro, etc. Proficiency with pipeline orchestration tools More ❯

Python, SQL and programming skills Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training More ❯

Python, SQL and programming skills Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training More ❯

programming languages such as Python, Java, TypeScript, and Go, and have experience with REST APIs and databases. You understand generative AI methodologies such as RAG, fine-tuning, agents, reasoning workflows, and more. You plan architecture and software with foresight to ensure automation, stability, and maintainability. Knowledge of cloud technologies (Azure More ❯

our analytics) OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past) Prompt Engineering Weaviate (we use it for RAG in LLM powered tasks and for hybrid searches) Kubernetes (we run Weaviate and other specific services on Kubernetes) CircleCI DataDog Auth0 (we use it, but More ❯

current with the Foundation Model ecosystem and applying these in practical, innovative ways. Experienced with Large Language Model projects, including API integration, prompt engineering, RAG, fine-tuning, and AI project management. From an engineering background or capable of building technical solutions with strong engineering principles for robustness, trustworthiness, and scalability. More ❯

novel, real world use cases. Experience delivering Large Language Model projects with customers, including LLM API integration, current knowledge of foundation models, prompt engineering, RAG, fine tuning, and managing AI projects. You either come from an Engineering background, or your desire to ship working solutions has allowed you to build More ❯

stack: Python, LlamaIndex/LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, React. You have hands-on experience working with LLMs, RAG architectures, NLP, or applying Machine Learning to solve real-world problems. You have a strong track record of building datasets for training and/or More ❯

language capabilities of large language models (LLMs) with the logical reasoning power of symbolic AI. This role is crucial in developing the next generation of decision intelligence for high stakes applications, where explainability, determinism, and precision are key. Role Specification As an R&D Engineer at Rainbird, you … evolution. The role demands expertise in LLM optimization techniques including fine-tuning on domain-specific data, crafting robust prompting strategies, and implementing retrieval-augmented generation style architectures. You'll apply these techniques to enhance decision accuracy while maintaining deterministic behavior where required. Your work … Huggingface), and a solid grasp of natural language processing techniques to enhance machine understanding and interaction. Knowledge of vector databases, embeddings, and retrieval-augmented generation style architectures. A proven track record of conducting rigorous research and translating theoretical findings into practical, solutions that drive More ❯

businesses. In this role, you will innovate in fast-moving AI research fields, focusing on integrating structured and unstructured information into AI systems (e.g., RAG techniques), with immediate application to Amazon products. If you have deep expertise in LLMs, natural language processing, and machine learning, this could be the perfect More ❯

fields of current AI research, in particular in how to integrate a broad range of structured and unstructured information into AI systems (e.g. with RAG techniques), and get to immediately apply your results in highly visible Amazon products. If you are deeply familiar with LLMs, natural language processing and machine More ❯

snowflake, talend, databricks, salesforce, hubspot, SaaS, data lakes, apis, adtech, GDPR, CCPA, B2B, Sales Consultant, Account Manager, DataOps, CICD, DevOPs, CI/CD, GenAI, RAG, AWS, Azure, Apache, Spark, Kafka – UK Wide - £80,000-£95,000 + OTE Our large Microsoft Partner client requires a Senior Data Analytics Sales Consultant More ❯

cloud. In this role you will You'll have the opportunity to work on a mixture of the following: Generative AI Design and develop RAG based applications. LLM fine-tuning, including preparation of training sets from internal data Agent based applications Evaluating use-case specific LLMs AI/ML NLP … required skills to achieve our goals: Bachelor's degree in computer science Extensive experience working in AI/ML Generative AI: Demonstratable experience of RAG, including chunking strategies, vectorising and indexing data, retrieval strategies and reranking, prompting strategies, function calling. Our current tech-stack is OpenAI, LangChain, Azure More ❯