Xinran Xu
Technical Lead at Megvii Technology Inc.
Haidian District, Beijing, China
Summary
👤
Senior🎓
Top SchoolXinran Xu is a Technical Lead at Megvii Technology Inc., where he currently leads a 10+ person team to build a fast feature search system over billions of faces and an object storage system for billions of small images. With 13 years of experience and proficiency in Go, Python, and JavaScript, he excels at rapid prototyping across frontend, backend, and distributed systems. A Tsinghua University CS graduate, he combines hands-on engineering with scalable architecture and reliability. In addition to his work at Megvii, he contributes to open source, notably addressing low-level FFmpeg bindings in PyAV as a backend developer—fixing return types, build-related issues, and PTS handling improvements. He is based in Beijing's Haidian District, bringing a strong blend of leadership, systems, and research-focused engineering to large-scale ML and data infrastructure.
13 years of coding experience
5 years of employment as a software developer
Bachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Tsinghua University
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (4)
cython10
ffmpeg10
python10
c-lib9
Programming languages (10)
Github contributions (5)
PyAV-Org/PyAV
Jul 2015 - Feb 2016
Pythonic bindings for FFmpeg's libraries.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5 commits, 4 PRs in 7 months
Contributions summary:Xinran primarily contributed to the pyav project by addressing low-level details related to FFmpeg bindings. Their work included fixing return types, adding library directories for compilation, and resolving a refactoring error in the build setup. They also made an ad-hoc fix for an analyze limit and added a flag to improve the process of obtaining PTS (Presentation Time Stamps).
ffmpegpyavpythonpythonic
MegEngine/Hub
Nov 2020 - May 2022
基于旷视研究院领先的深度学习算法，提供满足多业务场景的预训练模型
Contributions:4 reviews, 5 commits, 3 PRs in 1 year 6 months
deep-learningmodelmachine-learning
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