NLP / AI Engineer (Offline Intelligence System)
We are looking for an experienced NLP / AI Engineer to design and build a fully offline intelligence system using a private library of 200+ historical and classical text volumes. The role covers the full pipeline: high-precision OCR, structured text extraction, LLM fine-tuning, citation-accurate RAG, and a standalone desktop application. - Responsibilities • Process large collections of PDF volumes (thousands of pages) with high-accuracy OCR. • Clean and normalize text by removing footnotes, editor notes, and modern annotations while preserving core content. • Structure and embed rich metadata (author, title, volume, page, date). • Fine-tune open-source LLMs (LLaMA, Mistral, or similar) for historical linguistic patterns. • Build citation-strict RAG systems with precise references for every response. • Develop a 100% offline desktop interface with automated ingestion pipelines. • Iteratively refine model performance through continuous testing and collaboration. - Requirements • Proven experience in NLP and LLM fine-tuning (LoRA / QLoRA, quantization). • Strong background in RAG systems and vector databases. • Hands-on experience with high-precision OCR for complex documents. • Proficiency in Python for local deployment (PyQt, Streamlit, or similar). - Application • Please submit a brief description of your technical approach and relevant experience. Apply tot his job