Zhibo Wang is a Senior Research Scientist and PhD-trained machine learning engineer with a decade of experience building and scaling ML systems across top tech and pharma companies. Based in the San Francisco Bay Area, he has led GenAI product development and ranking infrastructure at Meta—driving Reels and Instagram relevance improvements—and contributed to ads recommendation and bidding at ByteDance. His work blends deep research (LLM training, transformers, sequence models) with pragmatic engineering—shipping retrieval, ESR/LSR ranking funnels, value models, and production-ready infrastructure. Earlier roles at Merck and Intel show strong interdisciplinary chops: healthcare sequence learning and a 1.4M-image dataset plus 20x speedups in chip-design validation using CV and autoencoders. Colleagues rely on him to turn research into measurable product value—true to his GitHub credo of "more efficient, more values." He pairs rigorous academic training in CS and Math with a proven track record of moving complex ML research into live systems.
10 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Central Florida
Contributions:2 releases, 32 PRs, 1061 pushes in 5 months
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