Summary
Angel Yang is a software engineer with a decade of experience who blends Stanford Ph.D.-level expertise in materials science and high-performance computing with hands-on production work in large-scale recommendation systems. Currently at Meta, Angel focuses on recommendation infrastructure and previously shipped latency- and accuracy-improving models and real-time indexing systems at Uber. Trained in chemical engineering and computer science (Ph.D. Stanford, MS Georgia Tech), Angel uniquely bridges wet-lab research—having led a chemistry lab and published multiple first-author papers—with scalable ML engineering for online systems. Based in Palo Alto, he excels at translating complex scientific models into efficient, production-ready services and is comfortable operating across research, backend systems, and large distributed pipelines.
10 years of coding experience
1 year of employment as a software developer
Bachelor of Science (B.S.), Chemical Engineering, 3.9/4.0, Bachelor of Science (B.S.), Chemical Engineering, 3.9/4.0 at National Taiwan University
Master of Science - MS, Computer Science, 3.7/4.0, Master of Science - MS, Computer Science, 3.7/4.0 at Georgia Institute of Technology
Doctor of Philosophy (PhD), Chemical Engineering, Doctor of Philosophy (PhD), Chemical Engineering at Stanford University
mandarian, English, Mandarin