Luyang Liu
Senior Software Engineer at Epic Games
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolLuyang Liu is a senior software engineer in Seattle with eight years of experience building large-scale, cloud-native services and public RESTful APIs—primarily within Azure and Microsoft’s identity and billing platforms. He now applies that expertise to Fortnite’s e-commerce systems at Epic Games, bringing a track record of designing highly available microservices and shipping production-grade APIs. Hands-on in back-end engineering and machine learning infrastructure, he has contributed to the OneFlow deep learning framework by implementing data loaders and improving core documentation. Known for strong collaboration across product and platform teams, he balances pragmatic engineering with attention to reliability and developer experience. Beyond production systems, his open-source contributions show curiosity about ML tooling and a habit of documenting work for wider reuse.
8 years of coding experience
7 years of employment as a software developer
University of California, Los AngelesBeijing No.2 middle school
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (15)
tensorrt10
data-preprocessing10
data-loading10
pytorch10
machine-learning10
tensor10
deep-learning10
dataprep10
preprocessing10
operation10
load-data10
python10
preprocess10
documentation9
tensorflow9
Programming languages (5)
Github contributions (5)
Oneflow-Inc/oneflow
Jul 2020 - Jan 2023
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:1582 reviews, 1144 commits, 451 PRs in 2 years 6 months
Contributions summary:Luyang primarily focused on developing and improving the core functionality of the deep learning framework "OneFlow". They implemented data loading routines for MNIST and other datasets, integrating libraries like `tqdm` and `requests` for data fetching and processing. Furthermore, they contributed to code documentation by adding detailed documentation to multiple modules covering topics like environment utilities, function utilities, configuration, session, and layer configurations.
caffe2tensorflowframework-learningchainerdeep-learning-framework
Flowingsun007/littleSpiders
Mar 2018 - Mar 2019
Contributions:19 commits, 15 pushes, 1 branch in 1 year
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