Louie Zhang
About Louie Zhang
Louie Zhang is a Senior Machine Learning Engineer at Sift, where he specializes in developing machine learning systems and bot detection technologies. He has extensive experience in data science and software engineering, having previously worked at LinkedIn and Peerspace.
Work at Sift
Louie Zhang has been employed at Sift as a Senior Machine Learning Engineer since 2020. In this role, he works with a large and complex Java codebase to support the production machine learning system. He is part of the ML Platform, Core Data Science, and Account Defense teams. Zhang designed and built a streaming-based bot detection system from scratch, employing deep learning techniques to classify complex bot behaviors in real-time. His contributions are integral to enhancing the security and efficiency of Sift's machine learning operations.
Education and Expertise
Louie Zhang holds a Bachelor's degree from the University of Chicago. He also studied abroad at Renmin University of China. His educational background provides a strong foundation in data science and machine learning, which he applies in his professional roles. Zhang's expertise encompasses a wide range of technologies, including Apache Flink, Kafka, Java, Bigtable, Redis, and TensorFlow, which he utilizes in developing machine learning models and systems.
Background
Prior to his current position at Sift, Louie Zhang worked at several notable companies in the San Francisco Bay Area. He served as a Data Scientist and Software Engineer at LinkedIn from 2014 to 2017, where he contributed to the development of machine learning models and services aimed at preventing account takeover abuse. Following his tenure at LinkedIn, he worked as a Senior Data Engineer and Software Engineer at Peerspace from 2018 to 2020, before moving to a Staff Engineer role at a Stealth Mode AI Startup for 11 months.
Achievements
During his career, Louie Zhang has made significant contributions to machine learning and data engineering. At Sift, he developed a streaming-based bot detection system that utilizes deep learning for real-time classification of bot behaviors. His work at LinkedIn involved creating machine learning models that effectively handle hundreds to thousands of events per second, enhancing the platform's security measures. These achievements reflect his capabilities in building robust machine learning systems.