Shengjia Yan
Software Development Engineer II at Amazon
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolShengjia Yan is a Software Development Engineer II at Amazon with a decade of experience building scalable back-end systems and data-driven features. He brings hands-on expertise in ML model development—particularly RNNs and Deep Knowledge Tracing—from an active GitHub repo that blends research and practical experimentation. His Amazon work spans payments, seller growth, and business reporting where he shipped production services, improved API reliability, and automated infrastructure with AWS CDK. A NYU MS graduate with earlier experience delivering large-scale education platforms in China, he pairs strong research roots in NLP and encrypted traffic analysis with pragmatic product delivery. Outside work he’s a persistent open-source contributor and, perhaps unsurprisingly, a committed ramen aficionado who’s open to referrals.
10 years of coding experience
6 years of employment as a software developer
Master of Science - MS Computer Engineering, Master of Science - MS Computer Engineering at New York UniversityBachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at Southeast University
Chinese, English
Stackoverflow
322reputation
19kreached
5answers
2questions
Github Skills (13)
pytorch10
machine-learning10
rnn-model10
deep-learning10
tensorflow10
python10
n10
dimensions6
nlp6
language-model6
ngram6
r6
computer-vision4
Programming languages (9)
Github contributions (5)
yanshengjia/ml-road
Oct 2017 - Nov 2020
Machine Learning Resources, Practice and Research
Role in this project:
ML Engineer
ML EngineerContributions:87 commits, 87 pushes, 1 branch in 3 years
Contributions summary:Shengjia primarily contributed to machine learning model development and experimentation within the repository. The commits involve implementing and modifying deep learning models, specifically focusing on recurrent neural networks (RNNs) for sequence learning tasks. The user added code for Deep Knowledge Tracing (DKT) and Backpropagation Through Time (BPTT), indicating experience in developing and applying advanced machine learning techniques.
nlppytorchpythondata-sciencedeep-learning
yanshengjia/artificial-intelligence
Apr 2017 - Nov 2020
Contributions:43 commits, 1 PR, 66 pushes in 3 years 7 months
artificialmachine-learningartificial-intelligence-projectsseuartificial-intelligence
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