About

Arpit Gole is a highly skilled Machine Learning Engineer with a passion for building Reinforcement Learning and Artificial Intelligence technologies that have real-world impact. With a deep understanding of statistical models, machine learning stack, and phases of machine learning workloads, Arpit is able to deliver revolutionary products. Currently working at Maptek, Arpit is spearheading the research and development of spatial domain models for geological resources, revolutionizing orebody modeling by using deep learning to generate classified domain models and ore grade estimation systems directly from spatially referenced mining/geological data. He has also designed a real-time data pipeline to process large geological datasets using widely acceptable geological assumptions. Arpit has previously worked as a Graduate Researcher at Maptek, where he developed a novel workflow to impute missing geological data that makes geological sense. He has also worked as a Machine Learning Engineer at Red Marker, where he implemented an end-to-end Natural Language Processing (NLP) workflow to bring down the false positive rate by more than 50% of the ecosystem in detecting language issues. He formulated various custom processing rules for client-specific needs to better identify irregularities in compositions related to legal/marketing. Arpit's education includes a Master of Machine Learning in Artificial Intelligence from the University of Adelaide, which he is due to complete in December 2022. He also holds a Bachelor of Technology in Computer and Information Sciences from Atria Institute of Technology and completed his 12th grade from Kendriya Vidyalaya. Arpit's tech stack includes ML, Reinforcement Learning, AWS, Python, Research Scientist, NLP, Deep Learning, and Computer Vision. With 3.36 years of relevant experience, Arpit is a highly skilled Machine Learning Engineer with a passion for building innovative AI technologies.