About

Jeffrey Cordero is a highly skilled software engineer and machine learning generalist with a passion for back-end software development and machine learning. He is a graduate of Texas A&M's honors computer science program, graduating summa cum laude, with deep learning research presented in multiple published papers on developing deep learning hardware. Currently working at Facebook as a Software Engineer / Machine Learning Generalist, Jeffrey is responsible for improving integrity and privacy within the People You May Know product. In his current role, he builds and leverages machine learning models to detect and combat fake and spam friending within a high-performance recommender system. He has also worked as an Engineer on PYMK privacy, where he applied static lineage tooling to automatically detect potential privacy violations across PHP and C++ codebases. As a Better Engineering Lead, Jeffrey has led multiple team-wide initiatives for improving code quality and developer efficiency. Prior to joining Facebook, Jeffrey worked as a Software Engineering Intern at ExxonMobil, where he was a part of the High-Performance Computing team. Here, he developed parallel scripts for automated and optimized big data transfer between large MySQL and Hadoop Hive databases. He also implemented Hadoop Hive for data analysis and pattern identification to help resolve unnecessary and/or poorly optimized files on a petabytes scale Lustre file system. Jeffrey has a diverse educational background, with a degree in Informatics from the University of Edinburgh and a Bachelor of Science in Computer Science from Texas A&M University. He is highly skilled in ML, Software Engineering, Backend, Deep Learning, iOS, Mobile, Research Scientist, PHP, Android, Objective-c, Javascript, Frontend, Web, Hadoop, Big Data, MySQL, Apache Hive, Python, and Java. With over four years of relevant experience, Jeffrey is seeking meaningful software engineering roles that provide great worth to his employer while expanding his own skill base.