Mike Ling
Site Reliability Engineering Manager at 美团
Jiangxi, China
Summary
🤩
Rockstar🎓
Top SchoolMike Ling is a Site Reliability Engineering Manager with 13 years of experience building and operating resilient infrastructure across companies like Meituan and Agora. He combines deep networking knowledge (Cisco/Huawei switches and routers) with hands-on SRE and DevOps practice, and has led teams to improve reliability at scale. An active open-source contributor, he has made notable back-end and tooling contributions to Mozilla projects like Treeherder and perf tooling, and implemented performance-sensitive KNN solvers for the Shogun ML toolbox during a Google Summer of Code. Based in Jiangxi, China, he balances leadership with coding—often diving into Python, C++ and system-level optimizations—and brings a practical focus on maintainability and performance from research-grade ML libraries to production CI systems.
13 years of coding experience
1 year of employment as a software developer
Networking, and Programing, Networking, and Programing at North China Institute of Aerospace Engineeringpostgraduate, Internet Of Things, postgraduate, Internet Of Things at Nanchang HangKong University
English, Chinese
Github Skills (23)
artificial-intelligence10
c-language10
python10
apidoc10
django10
machine-learning10
api10
cprogramming-language10
data-science9
javascript9
python-requests9
http-request9
data-structures8
continuous-integration8
uid8
Programming languages (10)
Github contributions (5)
mozilla/treeherder
Apr 2015 - Oct 2018
A system for managing CI data for Mozilla projects
Role in this project:
Back-end Developer
Back-end DeveloperContributions:46 commits, 49 PRs, 99 comments in 3 years 5 months
Contributions summary:Mike primarily focused on back-end development tasks within the `mozilla/treeherder` repository. Their contributions involved modifying Python code, particularly within the `treeherder/etl` directory, to add timeouts to requests, validate revisions, and implement new endpoints for the API. The user also made changes to front-end JavaScript code and HTML templates, including the addition of a measure selection tool in the UI.
reactpythondjango-rest-frameworkdjangodocker
shogun-toolbox/shogun
Feb 2017 - Dec 2017
Shōgun
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:34 commits, 28 PRs, 213 comments in 10 months
Contributions summary:Mike primarily focused on implementing and refactoring KNN solvers within the Shōgun machine learning toolbox. Their work included creating a new KNNSolver, moving related code, and implementing specific solvers like CoverTreeKNNSolver and KDTreeKNNsolver. The user also added tests for KNN solvers, fixing errors, and refactoring to use SGVector for better memory management. This indicates a focus on improving the performance and functionality of core machine learning algorithms within the Shōgun framework.
cmakedata-sciencegunc-plus-plusmachine-learning
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