5 of 5 Remote Retrieval-Augmented Generation Jobs in Cambridge

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 ❯

cross-functional teams. Experimental Approach: A passion for rapid iteration, learning from experiments, and data-driven development. Preferred Qualifications Experience designing RAG (Retrieval-Augmented Generation) or CAG systems using vector databases and hybrid retrieval techniques. Knowledge of LLM security challenges, including prompt More ❯

driven data analytics and business intelligence tools to derive valuable insights from data. Promote data-driven decision-making across the organisation. Operationalise ML, GenAI & RAG - strengthen our LLM-based assistant so colleagues can ask plain-English questions and get clear answers Implement data quality management processes to identify and rectify … of initiative, along with excellent organisational skills. Are highly proficient in spoken and written English. With essential experience in Have hands-on experience with RAG architectures (LangChain/LlamaIndex) and vector DBs (pgvector); embedded model fine-tuning & embeddings workflow. Developing and working with a variety of databases and data sets. More ❯

supporting cutting-edge discoveries. Your responsibilities include creating and maintaining AI-ready data flows, designing data architectures, enabling AI-driven analytics, operationalizing ML, GenAI & RAG, managing data quality, developing data access libraries and APIs, and advocating AI-first practices. You will collaborate with multiple teams, ensuring data infrastructure supports our … and passion for data as a resource. Proactive problem-solving skills and high initiative. Excellent English communication skills. Essential Experience Hands-on experience with RAG architectures (LangChain/LlamaIndex), vector DBs, model fine-tuning & embeddings workflows. Developing and optimizing high-volume data pipelines, large datasets, big-data architectures. Supporting AI More ❯

looking for an experienced ML engineer to help build and scale GenAI features across real products. You’ll be hands-on with NLP pipelines, RAG systems, LLM deployment, and AI infrastructure, working closely with product and platform teams to turn ideas into features. It’s the kind of role where … your code ships and your input shapes the roadmap. 🚀 Expect work across: GenAI + LLM tooling (vLLM, LangChain, HuggingFace) RAG systems, embeddings, reranking NLP tasks like summarisation, classification, sentiment Scalable deployment in AWS (with support from DevOps) Cross-team collaboration and mentoring Why join? Own and build GenAI features that More ❯