Chien Yu
軟體工程師 at 谷歌
New Taipei, Taiwan
Summary
👤
Senior🎓
Top SchoolChien Yu is a seasoned software engineer with about 10 years of experience building high-throughput backend services and cross-platform client modules, currently working at Google after a senior engineering role at Trend Micro. He specializes in C/C++ and Rust, having led a major migration of a service handling 7+ billion daily requests to Rust and successfully moved an internal EC2 service to EKS for better scalability. His background includes 3+ years developing L2/L3 switch software with SONiC, strong test-driven practices, and hands-on experience with Python, Shell, Docker, Kubernetes, and AWS. An active open-source contributor, he has added data-preparation and speech enhancement work to the popular SpeechBrain toolkit, showing practical ML tooling chops beyond systems engineering. Colleagues rely on him for pragmatic, reliable solutions—he even proposed an AI PoC adopted company-wide—bridging low-level networking work with cloud-native and ML-adjacent initiatives.
10 years of coding experience
6 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at National Taiwan University of Science and Technology
English, Chinese
Github Skills (16)
data-preprocessing10
pytorch10
machine-learning10
speech-enhancement10
audio-processing10
dataprep10
frequency-analysis9
spectral9
spectrum9
spectra9
transformers9
mask-rcnn9
spec9
faster-rcnn9
data-engineering8
Programming languages (2)
Github contributions (5)
speechbrain/speechbrain
May 2020 - Nov 2020
A PyTorch-based Speech Toolkit
Role in this project:
ML Engineer
ML EngineerContributions:56 commits in 6 months
Contributions summary:Chien's commits primarily involve data preparation scripts for the DNS challenge dataset, a speech enhancement task. These scripts prepare CSV files, split data into segments, and mix training data. Furthermore, the user modifies the model for spectral enhancement by adding the CNNTransformerSE model and making modifications to the processing workflow. Finally, the user also adds the PESQ and STOI metric evaluation.
voice-recognitionasrspeech-recognitionspeech-separationspeaker-verification
jerrygood0703/speech-enhancement-WGAN
Aug 2017 - Apr 2018
Contributions:32 commits, 26 pushes, 4 branches in 8 months
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