4 of 4 Retrieval-Augmented Generation Jobs in Scotland

Conduct research on the latest AI advancements and implement innovative solutions. Assist in fine-tuning large language models (LLMs) and retrieval-augmented generation (RAG) systems. Optimize model performance and work on deployment strategies using cloud-based AI solutions. Support MLOps best practices to streamline AI development workflows. Stay updated with the latest advancements in … in AI/ML development. Generative AI experience with Hugging Face, fine-tuning open-source LLMs like Mistral/Llama/Gemma/Phi/Qwen, vLLM, Text Generation Inference, unsloth, LoRA, adapters, DPO, ORPO, hugging face inference endpoints, LlamaIndex Experience with embeddings, vector databases, and deep learning models. Hands-on experience with cloud AI services (AWS, GCP More ❯

You'll work on projects at the cutting edge of AI, from natural language processing (NLP) and computer vision to Retrieval-Augmented Generation (RAG) and explainable AI. You'll be part of a collaborative environment where mathematical rigour meets practical innovation, building systems that make a measurable difference. What You'll Do Research & Develop … solutions for document intelligence, information retrieval, and automation. Build and enhance NLP and computer vision systems to extract, classify, and structure data from unstructured documents. Work with RAG architectures, implementing advanced document chunking, GraphRAG, and ScaNN to boost retrieval precision. Deploy AI-powered bots and web applications on cloud platforms (e.g., Microsoft Azure). Develop systems … NLP, computer vision, and retrieval methods. Ability to turn theory into practical, deployable systems. Desirable Experience with Microsoft Azure or other cloud platforms. Knowledge of vector search, RAG pipelines, and document chunking strategies. Familiarity with advanced search techniques such as anisotropic vector quantisation. Interest in explainable AI and model interpretability. Why Join Us? Work on groundbreaking AI projects More ❯

models using unsupervised learning, deep learning (e.g. auto-encoders), and novelty detection techniques. Lead a team of Data Scientists Drive innovation in LLM-based security automation, including prompt engineering, RAG pipelines, and fine-tuning of models. Collaborate with Data Engineers to build scalable, secure, and production-ready ML pipelines on GCP. Partner with cyber defence, risk, and compliance teams to More ❯

models using unsupervised learning, deep learning (e.g. auto-encoders), and novelty detection techniques. Lead a team of Data Scientists Drive innovation in LLM-based security automation, including prompt engineering, RAG pipelines, and fine-tuning of models. Collaborate with Data Engineers to build scalable, secure, and production-ready ML pipelines on GCP. Partner with cyber defence, risk, and compliance teams to More ❯