Summary
Junyan Xu is a software engineer with 11 years of experience at the intersection of large-scale ML systems and systematic finance, currently contributing to TPU-based inference and Gemini serving at Google and DeepMind. He has built production ML infrastructure—model monitoring, abuse detection, and high-performance inference on TPUs—while earlier applying quantitative engineering to equity alpha and credit risk at Cubist, J.P. Morgan, and Goldman Sachs. Trained in financial mathematics (University of Chicago) with a CS minor from Tsinghua, he blends rigorous quantitative thinking with systems-level implementation. Based in Mountain View, he develops for fun and brings a practical, research-aware approach to squeezing performance from specialized hardware for real-world deployments.
11 years of coding experience
8 years of employment as a software developer
High School, High School at Chengdu No.7 High School
Minor Degree of Computer Science Computer Science, Minor Degree of Computer Science Computer Science at Tsinghua University
master financial mathematics, master financial mathematics at University of Chicago