Generare augmentată prin preluare (RAG) Jobs

Developed a healthcare AI application for lung disease classification using chest X-ray images, combined with an interactive medical chatbot and voice assistant. The classification component analyzes chest X-ray images and predicts the corresponding lung disease category. Alongside the classification model, I was responsible for developing the AI Chatbot and RAG system, allowing users to ask questions about lung diseases, symptoms, and medical information. I implemented Retrieval-Augmented Generation (RAG) to connect the chatbot with a medical knowledge base, enabling it to retrieve relevant information and generate more informative and context-aware responses. The system also included a Voice Assistant to provide a more natural voice-based interaction with the user. Key Features: Che...

I’m looking to turn our scattered know-how—hundreds of PDFs, policies, detailed reports, emails, meeting minutes, and assorted documentation—into a single Retrieval-Augmented Generation assistant that answers questions instantly and finds the exact source passage behind every reply. What I already have in mind • Ingestion pipeline that automatically pulls new or updated PDFs, email archives, and other internal files, cleans the text, and embeds it in a vector store (FAISS, Pinecone, or a similar tool). • A lightweight search layer so staff can type a query and receive both a concise answer and the ranked source documents. • Chat-style interface (web or Slack/Teams bot) backed by an LLM with citations, guardrails, and role-based access. • Modular...

I’m looking for an experienced **AI trainer/mentor** who can provide structured, one-to-one online training and help me progress from AI fundamentals to practical, job-ready skills. The objective is not simply to complete a course or learn theory. I want to **understand AI concepts clearly, gain hands-on experience through practical projects, and develop skills that I can confidently demonstrate during job interviews**. The training should be beginner-friendly and gradually progress from fundamentals to more advanced and practical topics. ### Learning Areas The training should cover: **1. AI Fundamentals** * Artificial Intelligence concepts and terminology * How modern AI systems work * Real-world AI use cases * AI models, data, training and inference * Responsible AI, governan...