Key Responsibilities Develop and deploy machine learning and GenAI solutions using Python Design and optimize prompt engineering strategies for LLM-based applications Build document extraction, parsing, and chunking pipelines for structured and unstructured data Train, evaluate, and fine-tune ML models; manage tagging and labeling workflows Implement embedding generation and vector search solutions Integrate ML models with Vector DBs and MongoDB Ensure code quality, scalability, and production readiness Required Qualifications Expert-level proficiency in Python Strong experience in model training, evaluation, and tagging workflows Hands-on experience with document extraction and chunking techniques Solid understanding of ML algorithms and Generative AI concepts Experience working with Vector Databases and/or MongoDB The ideal candidate will have deep expertise in Python, hands-on experience in model training, document processing pipelines, and strong knowledge of vector databases and modern ML/GenAI frameworks.