AI Developer Needed for Document Embedding & Semantic Search Module

We are seeking an AI/ML Developer to build a Document Embedding & Semantic Search Module for an internal document intelligence project. The goal is to enable efficient semantic search across uploaded documents by generating vector embeddings and retrieving the most relevant content based on user queries. Responsibilities: • Document ingestion and processing (PDF, DOCX, TXT) • Text extraction and intelligent chunking • Embedding generation using modern embedding models • Vector database integration (FAISS, ChromaDB, or similar) • Semantic search implementation • Retrieval of top relevant document sections based on similarity • Clean, maintainable, and well-documented code Deliverables: • Working document embedding pipeline • Vector storage implementation • Semantic search functionality • Source code and setup instructions • Basic testing and validation