Yen-shi Wang is a software engineer with a decade of experience focused on systems, performance optimization, and cloud computing, currently working at NVIDIA and pursuing an MS at Carnegie Mellon. He has a strong background in low-level and ML-related optimization, having implemented numerous compiler passes and an 8-bit quantization flow for NVDLA, and has productionized PyTorch-based OCR pipelines deployed in Docker for real customers. Yen-shi’s mix of academic teaching, quantitative research at WorldQuant, and hands-on engineering across startups and a major GPU company gives him a rare blend of algorithmic rigor and production performance tuning. Based in Mountain View, he brings practical experience scaling ML workloads and squeezing performance from hardware-software stacks, with a demonstrated ability to turn prototypical models into deployed systems.
10 years of coding experience
1 year of employment as a software developer
Bachelor's degree, Electrical and Electronics Engineering, Bachelor's degree, Electrical and Electronics Engineering at National Taiwan University
Master of Science - MS, Electrical and Computer Engineering, Master of Science - MS, Electrical and Computer Engineering at Carnegie Mellon University
Contributions:4 reviews, 31 commits, 3 PRs in 3 years 8 months
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