Victor Shi
Software Engineer at TikTok
Berkeley, California, United States
Summary
👤
Senior🎓
Top SchoolVictor Shi is a software engineer based in Berkeley with eight years of experience building ML, AI metadata, backend, and cloud systems across startups and large tech firms. He has applied research experience from UC Berkeley—contributing to zero-knowledge rollup benchmarks and synthetic assets research—and brings that rigor to production work at Applied Intuition after roles at TikTok and Intel. His background spans confidential computing, product security, and cloud infrastructure, reflecting a blend of security-minded engineering and scalable system design. Victor is comfortable in open-source and research-adjacent environments, having contributed to backend and infra projects like CambioML and the Open Computing Facility. He pairs academic depth (CS PhD-level training at Berkeley) with hands-on delivery across internships and product teams, and famously summarizes his approach with a philosophical bent: "The unexamined life is not worth living."
8 years of coding experience
2 years of employment as a software developer
Undergraduate Computer Science, Undergraduate Computer Science at UC Berkeley College of Computing, Data Science, and Society
Github Skills (63)
depth-estimation10
representation-learning10
multimodal10
information-theory10
foundation-models10
dropout10
chatbot10
chatgpt9
corruption9
meta-learning9
few-shot-learning9
robustness9
generative9
weakly-supervised-learning9
backbone8
Programming languages (4)
Github contributions (5)
bfshi/InfoDrop
Jun 2020 - Apr 2021
Code for our paper "Informative Dropout for Robust Representation Learning: A Shape-bias Perspective" (ICML 2020)
Contributions:15 commits, 4 PRs, 20 pushes in 10 months
meta-learningrobustnessshape-biasrepresentation-learningicml
bfshi/bfshi.github.io
Mar 2020 - Mar 2025
Contributions:62 pushes, 1 branch in 5 years 1 month
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