Peng Zhong is a software engineer with four years of professional experience building large-scale backend services and productionizing machine learning systems. He has delivered scalable personalization pipelines and microservices at Zynga and currently contributes to backend engineering at Uber. His background spans ML infrastructure (TensorFlow, Spark, Airflow) and cloud-native services (Go, Java, AWS, Docker, Terraform), enabling end-to-end deployment from models to reliable production APIs. Academically grounded with an M.Eng. from McGill and a B.E. from Shanghai Jiao Tong, he pairs research experience in coding schemes with practical system-building. Notably, he has moved between pure ML engineering and high-availability payment and infrastructure systems, demonstrating an ability to bridge data science and production-grade software. Based in Old Toronto, he focuses on scalable, observable systems that take prototypes through to robust, automated deployment.
4 years of coding experience
9 years of employment as a software developer
Master of Engineering (M.Eng.), Electrical and Computer Engineering, 4.0/4.0, Master of Engineering (M.Eng.), Electrical and Computer Engineering, 4.0/4.0 at McGill University
Bachelor of Engineering (B.E.), Information Engineering, 3.78/4.0, Bachelor of Engineering (B.E.), Information Engineering, 3.78/4.0 at Shanghai Jiao Tong University
Apache Spark - A unified analytics engine for large-scale data processing
Contributions:37 reviews, 4 PRs, 46 comments in 2 months
analyticspythondata-processingsqlapache
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