Zack Cao is a backend and infrastructure engineer with 10 years of experience building scalable, reliable services for tracking driving events and mileage, now working as a Member of Technical Staff in Menlo Park. He has designed and operated distributed systems and data pipelines at scale across Meta’s Superintelligence Lab and Microsoft, focusing on observability, autoscaling, CI/CD, and Kubernetes-driven model training and serving. Proficient in Java, Python, Scala and modern cloud tooling (AKS, Docker, Pulumi, Buildkite, Azure Data Factory) he bridges backend service design, infrastructure architecture and frontend experience when needed. Zack’s background includes capacity modeling, end-to-end training observability, and performance eval tooling for inference — skills that underscore a pragmatic approach to both production reliability and AI workflows. He pairs a Drexel M.S. in Computer Science with hands-on full-stack experience from startups to hyperscale teams, and often operates at the intersection of developer experience and ops. An understated strength is his ability to translate research-scale ML workloads into reproducible, observable pipelines on public clouds.
9 years of coding experience
6 years of employment as a software developer
Master of Science (M.S.), Computer Science, 3.8/4.0, Master of Science (M.S.), Computer Science, 3.8/4.0 at Drexel University
Bachelor of Engineering (B.E.), Computer Software Engineering, Bachelor of Engineering (B.E.), Computer Software Engineering at Hangzhou Dianzi University
Contributions:15 commits, 1 PR, 21 pushes in 1 year 10 months
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