5 of 5 Retrieval-Augmented Generation Jobs in Sheffield

/Vertex AI, including fine-tuning, vector search, and low-latency inference. Build end-to-end LLM applications, leveraging RAG (Retrieval-Augmented Generation), agentic workflows, and prompt engineering. Implement robust evaluation frameworks to monitor LLM quality, hallucinations, token usage, and content safety. Develop … Looking For Essential 5+ years' experience in machine learning engineering or applied AI roles. Recent, demonstrable experience with LLMs, Generative AI, and/or RAG-based systems. Strong Python skills using frameworks such as PyTorch, TensorFlow, Hugging Face, or Google GenAI. Experience with vector databases and retrieval-based ...

Practical experience with AWS (and ideally Terraform, GitLab CI). Experience with agentic systems or LLM-powered automation (e.g. tool-augmented LLMs, RAG workflows, agents for complex workflows). If this sounds like you, reach ...

Transformer-based text classification (BERT/DistilBERT/RoBERTa) • Fine-tuning classification heads • Embeddings + cosine similarity search • Supporting LLM-adjacent work (not deep RAG) Tech Python, sklearn, XGBoost/LightGBM, HuggingFace Transformers, BERT-family models, embeddings, cloud-based ML, CI/CD awareness. What They're Looking For • Strong ...

Developing and optimizing models for image recognition, object detection, and video analytics. NLP: Building sophisticated systems for sentiment analysis, entity extraction, semantic search, and RAG architectures leveraging LLMs. Generative AI: Exploring and implementing cutting-edge GenAI techniques for content creation, data augmentation, and innovative product features. SME Consulting & Mentorship … with Computer Vision tasks (e.g., CNNs, object detection models like YOLO). NLP: Expert practical experience in NLP techniques, including transformer models, embedding generation, and building complex text-based applications. 3. Leadership & Soft Skills Technical Leadership: Proven track record of leading complex data science projects from research ...

deployment. Deep knowledge of RAG Experience processing high volumens of documentation/text Strong knowledge of NLP and LLMs (transformers, fine-tuning, retrieval-augmented methods, agents). Experience conducting applied research and converting experimental outcomes into production systems. Familiarity with retraining workflows and performance monitoring. Understanding ...