Shengjie Luo is a Principal Software Engineer with nine years of experience specializing in resource management and scheduling for large-scale datacenters, cloud platforms, and microservice frameworks. A Carnegie Mellon MCDS alumnus with a Stanford cybersecurity certificate, he spent five years shaping VMware/Broadcom's vSphere resource scheduler and now tackles GPU and heterogeneous accelerator challenges powering the AI era. His work ranges from distributed scheduler simulators and Elastic DRS autoscaling to Kubernetes scheduler extenders in Project Pacific, demonstrating both algorithmic depth and production-grade systems delivery. Notably, he has hands-on experience applying ML and heterogeneous acceleration—evidenced by past SparkML and FPGA projects—to squeeze efficiency from high-throughput environments. Based in Mountain View, he blends research-driven problem solving with pragmatic engineering to optimize resource utilization at enterprise scale.
9 years of coding experience
9 years of employment as a software developer
Bachelor Computer Science, Bachelor Computer Science at Shanghai Jiao Tong University
High School Diploma, High School Diploma at High School Affiliated to Shanghai Jiao Tong University
Master Master of Computational Data Science (MCDS), Master Master of Computational Data Science (MCDS) at Carnegie Mellon University
Graduate Certificate Cyber Security, Graduate Certificate Cyber Security at Stanford University
Contributions:212 commits, 53 PRs, 208 pushes in 4 months
securitysjtunetwork-securitylabsecurity-system
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