Parth M.

Data Scientist and Machine Learning Engineer specializing in building production-grade ML systems across diverse domains including manufacturing optimization, anomaly detection, computer vision, NLP, and geospatial analytics. At Novelis Inc., I develop scalable, real-time ML pipelines integrating optimization techniques, computer vision, and AutoML methods deployed on cloud-native infrastructure.

Previously at the Ministry of Rural Development, I designed large-scale NLP and geospatial clustering models deployed at a national scale to optimize infrastructure planning and operational efficiency. My past experience also includes developing deep learning-based energy optimization solutions at ActiveBAS and delivering production ML services at scale, such as an air quality forecasting API at Blue Sky Analytics.

My academic research at Michigan State University focuses on advanced techniques, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Graph Neural Networks, and Semantic Segmentation. I have hands-on experience deploying models in cloud environments (AWS, Azure, GCP), alongside strong proficiency with Python, PyTorch, TensorFlow, SQL/NoSQL, and containerized applications.

Open to full-time roles as a Machine Learning Engineer, Applied Scientist, or Data Scientist in organizations tackling complex AI-driven challenges at scale.