Minli Zhu
YouTube Content Creator
Sunnyvale, California, United States
Summary
👤
Senior🎓
Top SchoolMinli Zhu is a senior software engineer and founder with 12+ years building high-reliability storage, cloud and data systems and a current founder of Spark Fit Silicon Valley, an O2O marketplace combining blockchain and ML/NLP to verify trust between fitness coaches and clients. She brings deep systems expertise from roles at Pure Storage, Google and NetApp—shipping kernel, storage and MySQL/CloudSQL improvements at petabyte scale—and has applied that rigor to low-latency financial systems and SRE work at eBay and LTSE. Her background blends academic research (PhD in network security and system design) with hands-on AI/ML, Web3 and LLM-Ops practice, and she maintains an active public presence through a technical YouTube channel and code contributions to Google projects. A notable throughline is translating research-grade ideas into production: from secure overlay networks in her dissertation to performance wins in Dataflow/Apache Beam and FlashBlade reliability tools. Based in Sunnyvale, she pairs systems-level depth in C/C++ and Go with modern cloud, big-data and security stacks to solve complex, customer-facing reliability problems.
12 years of coding experience
24 years of employment as a software developer
PhD Computer Science and Engineering (Network Security & System Design), PhD Computer Science and Engineering (Network Security & System Design) at University of California, RiversideMaster of Science - MS Computer Science and Engineering (Artificial Intelligence and Robotics), Master of Science - MS Computer Science and Engineering (Artificial Intelligence and Robotics) at Tsinghua University
Chinese, English, JapaneseGithub contributions (1)
google/mysql
Oct 2013 - Jun 2014
Contributions:9 commits in 8 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.