Jian Fu is a machine learning engineer with 10 years of experience building search and recommendation systems for large consumer platforms. He has driven relevance and performance improvements at Apple, BIGO and as an intern at Tencent, applying ML to web search, short-video recommendations, and query intent analysis. Jian contributes to open-source ML tooling—adding image encoders and advanced preprocessors to the GNES semantic search project—bringing practical, production-ready neural search experience. Based in San Jose, he blends a strong research foundation from Fudan University with hands-on engineering that bridges model development and system integration. He’s currently seeking internships or full-time roles and brings particular strength in image preprocessing and encoder design for semantic retrieval at scale.
10 years of coding experience
4 years of employment as a software developer
Master of Engineering - MEng, Artificial Intelligence, Master of Engineering - MEng, Artificial Intelligence at San José State University
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Fudan University
GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network.
Role in this project:
ML Engineer
Contributions:138 commits, 167 PRs, 134 pushes in 3 months
Contributions summary:Jian implemented and refined image preprocessors and encoders for the GNES project, specifically focusing on image-related functionalities. Contributions included adding an image encoder and preprocessor, refactoring a sliding window preprocessor, and integrating a weighted sliding preprocessor. These changes directly support the handling and processing of image data within the semantic search system, contributing to improved performance and feature set.
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