10 of 10 Retrieval-Augmented Generation Jobs in Hemel Hempstead

expertise in Python, React, and modern AI/ML development, including LLM frameworks, SDKs, and retrieval-augmented generation (RAG) systems. Key Responsibilities Design and develop scalable full-stack solutions involving both frontend (React/TypeScript) and backend (Python/Java). Build and optimize …/ML pipelines leveraging LLMs and RAG architectures. Develop SDKs and APIs to support AI-driven applications in resource-constrained or production-grade environments. Collaborate across engineering, product, and research teams to drive innovation in AI/ML-based products. Ensure high performance, testability, and reliability across the stack. ...

gatherings Salary: Senior: €130–150k base + growth trajectory Principal: €160–200k base + package discussion Tech: Python, JavaScript, Azure, AWS, AI, LLM's, RAG Industry: AI Consultancy The Role We're looking for talented engineers to join our customer-facing AI practice, from Senior Forward Deployed Engineers through … components, and solution standards AI Mastery & Innovation Implement AI solutions leveraging LLMs, foundation models, and retrieval-augmented generation (RAG) systems Design evaluation frameworks addressing bias, hallucination detection, and business impact Explore novel AI applications while integrating traditional ML techniques where appropriate ...

Responsibilities Design and implement AI/ML and Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor ...

/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 ...

production in large or complex organizations. Strong understanding of AI and machine learning technologies including natural language processing, generative AI, retrieval augmented generation and MLOps. Hands-on experience with cloud platforms, with a preference for Microsoft Azure. Excellent leadership and communication skills with ...

fine-tune LLM-based applications (chatbots, summarization, document Q&A, report generation, code assistants, etc.). Apply prompt engineering, RAG (Retrieval-Augmented Generation), and context-aware pipelines to ensure accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores … ethics, security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Partner with business stakeholders to identify and shape ...

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 ...