Jeremy Wiesner is a Staff Software Engineer and tech lead manager based in Seoul with eight years of experience building scalable, trustworthy ML infrastructure at Google. He has led teams that deliver core training, trust and responsible-AI systems as well as data ingestion and serving pipelines that powered sensitive features like elections and politics in Search. Prior to Google he combined hands-on engineering and program management at Coupang—shipping production BaaS and automated e-commerce purchasing systems—and earlier worked on high-performance simulation and structural engineering. Jeremy is comfortable driving both architecture and delivery across backend, metrics, and distributed systems; his open-source work on enhancing multi-tenant backend metrics (para) reflects a practical focus on observability and operational reliability. He holds an MS in Structural Engineering and a BS from UC Berkeley, bringing a discipline for rigorous modeling and scalable design to ML infrastructure. Colleagues describe him as a leader who turns complex, safety-sensitive requirements into reliable, production-ready systems.
8 years of coding experience
13 years of employment as a software developer
Bachelor of Science (B.S.), Major: Civil Engineering, Minor: Architecture, Bachelor of Science (B.S.), Major: Civil Engineering, Minor: Architecture at University of California, Berkeley
Multitenant backend server for building web and mobile apps rapidly. The backend for busy developers. (self-hosted or hosted)
Role in this project:
Back-end Developer
Contributions:14 commits, 7 PRs, 33 comments in 27 days
Contributions summary:Jeremy primarily focused on enhancing the backend server's metrics capabilities. They implemented app-specific settings for pushing metrics to Graphite, enabling more granular performance monitoring. The commits included adding listeners to manage app-specific Graphite settings and modifying the codebase to support these new settings. They also addressed issues related to reporter removal and chunk size for batch CRUD operations, improving the system's performance and reliability.
Contributions:1 PR, 23 pushes, 35 branches in 1 year 7 months
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