Vera Lin is an experienced machine learning engineer and founder based in the San Francisco Bay Area with 11 years of experience building production ML systems and data-driven products. She spent several years at Apple advancing natural language search, document understanding, ranking, and fraud detection for the App Store, and contributed research-grade tooling for on-device model robustness during a Google internship. Her academic work with Stanford SNAP and a Master’s in CS informs a strong foundation in graph analysis, interpretable few-shot learning, and document-embedding methods. Now founding Catalyst Home Ventures, she applies analytical rigor and ML-informed decision making to transform Bay Area properties for homeowners and investors. Colleagues describe her simply as someone who genuinely likes data—a trait that shows in both research and practical engineering that bridges prototypes to production.
11 years of coding experience
7 years of employment as a software developer
Software Engineering, Software Engineering at University of Waterloo
Master's degree Computer Science, Master's degree Computer Science at Stanford University
Implementation of Prototypical Networks for Few Shot Learning (https://arxiv.org/abs/1703.05175) in Pytorch
Contributions:20 pushes, 3 branches in 1 month
pytorchprototypical-networksarxivmeta-learningabs
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