Sam Denton
About Sam Denton
Sam Denton is a Senior Machine Learning Research Engineer at Scale AI, where he leads machine learning projects for the Enterprise Generative Platform team. He holds a Bachelor of Arts in Mathematics and Computer Science from Columbia University and has previously worked at Amazon and the U.S. Securities and Exchange Commission.
Current Role at Scale AI
Sam Denton serves as a Senior Machine Learning Research Engineer at Scale AI, a position he has held since 2023. He is based in San Francisco, California. In this role, he leads machine learning projects for the Enterprise Generative Platform team. His work focuses on applying machine learning techniques to real-world scenarios, contributing to the development of innovative solutions in the field.
Previous Experience at Amazon
Prior to his current role, Sam Denton worked at Amazon in various capacities. He was a Machine Learning Scientist from 2020 to 2021, where he contributed to machine learning initiatives for a year in Seattle, Washington. Before that, he served as a Machine Learning Scientist II for six months in 2021. Additionally, he worked in Software Development at Amazon from 2018 to 2019 for one year, gaining extensive experience in machine learning applications.
Education and Academic Background
Sam Denton studied at Columbia University, where he earned a Bachelor of Arts (B.A.) degree in Mathematics & Computer Science and Statistics. He also completed his high school education at The Urban School of San Francisco. His academic background provides a strong foundation in the principles of mathematics, statistics, and computer science, which he integrates into his professional work.
Early Career at U.S. Securities and Exchange Commission
In 2018, Sam Denton began his career as a Machine Learning Engineer at the U.S. Securities and Exchange Commission. He worked in this role for four months in the Greater New York City Area. This position marked the beginning of his journey in the field of machine learning, where he gained practical experience in applying machine learning techniques in a regulatory environment.