I'm Pakhee Sinha, an Aerospace Engineering undergraduate with hands-on experience building AI/ML systems for real-world scientific and defense applications. As a Research Collaborator with SRMSAT Club, I designed and built an end-to-end AI pipeline for lunar mineralogical mapping — integrating Chang'e-3 and LOLA datasets through data ingestion, multimodal fusion, and feature extraction, then training classification models and visualizing results through an interactive 3D platform. At IIT Madras Pravartak Technologies, I contributed to integrating AI algorithms with targeting and electromechanical systems for autonomous defense operations, working under strict R&D protocols. I'm proficient in Python, PyTorch, TensorFlow, and geospatial ML, with a growing focus on explainable AI, RAG architectures, and MLOps. I'm excited to bring this blend of applied AI engineering and domain-specific problem solving to an internship where I can contribute to production-grade ML systems.