Summary
Yibai Meng is a software engineer with nine years of experience specializing in ML model optimization and inference infrastructure for autonomous vehicles at Waymo. He holds degrees from Peking University and UC Berkeley and has a strong background in high-performance systems, demonstrated by GPU-accelerated FPGA placement work that reframed placement as a neural-network-style optimizer and earned a top IEEE journal publication. At ByteDance he implemented a C++ data-plane network verification algorithm that sped up topology modeling and invariant checks by over 500x and enabled real-time verification of a global network. Comfortable across C++, CUDA, and PyTorch-based pipelines, he blends research-grade algorithm design with production-focused implementation. Based in Mountain View, he gravitates toward problems that sit at the intersection of systems engineering and machine learning, often turning academic ideas into scalable, shipping code. Notably, he has a knack for simplifying complex toolchains by using Python extensions to keep developer ergonomics high without sacrificing performance.
9 years of coding experience
1 year of employment as a software developer
Master of Engineering - MEng, Electronic Engineering and Computer Science, 3.9, Master of Engineering - MEng, Electronic Engineering and Computer Science, 3.9 at University of California, Berkeley
Bachelor of Science - BS, Electrical and Electronics Engineering, 3.6 / 4.0, Bachelor of Science - BS, Electrical and Electronics Engineering, 3.6 / 4.0 at Peking University
High School Diploma, High School Diploma at Beijing No.4 High School