About

Clemente Cuevas is a highly skilled Senior Machine Learning Engineer with over a decade of experience building data-driven models and using data-driven techniques to solve real-world problems. Currently working at Interos Inc, he has a passion for applying machine learning and classical statistical techniques to solve problems for humans and other creatures. Clemente has a wealth of experience in various domains, including search, natural language processing, and big data. He has worked as an Applied Research Scientist and ML Engineer at Element AI, where he was involved in engineering machine learning features for Knowledge Scout, a knowledge management system for enterprise. He has also worked extensively on natural language processing for question answering, AI-assisted search and relevancy, semantic parsing, and automated knowledge base construction, among other areas. As a Lead AI Engineer at EruditeAI, Clemente engineered software systems and machine learning models for cataloguing and sharing individual knowledge across internal departments in large enterprises. He also conducted experimental research on applications of reinforcement learning systems to education and developed technology for assisting students to tutor their peers on mathematics problems. Clemente has a Bachelor of Science in Physics/Mathematics from the University of Florida, where he graduated in 2014. He has a keen interest in causality, the intersection of design and engineering, and the teachings of UNIX. His personal interests include music, games, and food. Clemente has extensive experience with a wide range of technologies, including ML, research scientist, AI, NLP, search, reinforcement learning, big data, Scikit, Pandas, Pytorch, Python, Docker, Elastic Search, Flask, and Java. With 10.70 years of relevant experience, he is a highly skilled and motivated professional who is passionate about using data-driven techniques to solve real-world problems.