Hengda Shi is a machine learning engineer with a decade of experience building production search and recommendation systems, currently on the search team at Meta after a multi-year tenure at ZipRecruiter. He led development of multi-task neural ranking models, position-debiasing techniques, and LLM-enabled job title discovery while driving search engine migrations and cross-team relevance interfaces. His work spans query understanding, ranking, and visual similarity models, grounded in an MS and BS in Computer Science from UCLA. Based in Mountain View, he blends research-minded experimentation with pragmatic deployment experience at scale, and has a knack for translating complex relevance problems into operational ML pipelines.
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