Juanli Shen
Software Engineer at Google
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJuanli Shen is a software engineer based in Sunnyvale with 11 years of experience building robust back-end systems at major tech companies, currently at Google. He has deep C++ systems expertise demonstrated by contributions to high-profile open-source projects like gRPC—where he improved load-balancing reliability—and TensorFlow/runtime, focusing on runtime performance and SavedModel execution. His background blends rigorous academic training (UIUC MS, Fudan CS, exchange at NUS) with hands-on internships at Facebook and Microsoft Research Asia, reflecting both research and production mindsets. Juanli’s work often targets subtle but critical reliability and performance edges, such as fallback mechanisms in balancers and HostBuffer behavior in runtimes. Comfortable navigating large, complex codebases, he repeatedly delivers clean refactors and clarifying changes that improve long-term maintainability. Colleagues would note his propensity to find and fix foundational issues that quietly improve system robustness at scale.
11 years of coding experience
1 year of employment as a software developer
Initial Major, Journalism, Initial Major, Journalism at Fudan UniversityUniversity of Illinois Urbana-ChampaignExchange Program, Computer Science, Exchange Program, Computer Science at National University of Singapore
wu
Stackoverflow
56reputation
11kreached
8answers
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Github Skills (24)
c-language10
back-end-development10
load-balancing10
c1110
ml10
c1710
mle10
tensorflow10
performance-optimization10
cprogramming-language10
grpc10
mlr9
machine-learning9
deep-learning9
data-structures8
Programming languages (7)
Github contributions (5)
grpc/grpc
Aug 2017 - Jan 2020
The C based gRPC (C++, Python, Ruby, Objective-C, PHP, C#)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 release, 369 commits, 426 PRs in 2 years 5 months
Contributions summary:Juanli primarily worked on the implementation of core gRPC features, specifically concerning load balancing policies. They refactored code to expect only backends, ensuring consistency within the pick-first and round robin policies. Additionally, the user added a fallback mechanism to the grpclb policy, enabling clients to utilize backends from the resolver if the balancer is unreachable. This work directly enhances the reliability and robustness of the gRPC framework.
objective-ccpppythongrpcphp
tensorflow/runtime
Nov 2020 - Jan 2023
A performant and modular runtime for TensorFlow
Role in this project:Back-end Developer
Back-end DeveloperContributions:13 commits in 2 years 2 months
Contributions summary:Juanli primarily contributed to the `tensorflow/runtime` repository by modifying core runtime functionalities. Their work involved clarifying the behavior of `HostBuffer` when empty, improving the readability of alignment operations, and memorizing data addresses. They also updated the `core_runtime` module, including reverting a change related to constant string tensors and clarifying value consolidation optimization. These changes suggest a focus on performance and optimization within the runtime environment.
runtimeperformantmodulartensorflow
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