Fan Xie is a software engineer with 9 years of experience building high-performance distributed systems and large-scale ML infrastructure, currently developing MPMD scheduling and orchestration for heterogeneous model training at ByteDance. Previously at Google and LinkedIn he drove autoscaling and resource management for streaming and advertising ML systems, and contributed substantial core code to Apache Kylin early in his career. He pairs systems-level expertise (YARN, Kubernetes, Flink/Samza) with hands-on ML systems work and a practical interest in performance tuning evidenced by competition wins and HPC contest placements. Fan also contributes front-end improvements to popular open-source projects like the Jellyfin Vue client, showing full-stack fluency beyond core infra. Trained at NYU with additional AI coursework from Stanford, he blends academic rigor with production-grade engineering.
9 years of coding experience
5 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at New York University
Bachelor's degree Computer Science, Bachelor's degree Computer Science at Sun Yat-sen University
Guangdong Experimental High School
Artificial Intelligence Graduate Certificate, Artificial Intelligence Graduate Certificate at Stanford University
Contributions:5 reviews, 10 commits, 1 PR in 28 days
Contributions summary:Fan primarily contributed to the development of the Jellyfin Vue web client by implementing new features related to metadata editing and the user interface. Their work included creating and modifying Vue components for metadata input and display, incorporating date pickers, and integrating image search functionality. They also focused on improving the user experience by adding features like scroll-based navigation and person editors. The user worked extensively with Vue.js, Vuetify components, and API integrations, as evidenced by file modifications across multiple components.
Contributions:117 pushes, 1 branch in 2 years 7 months
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