Shuning Jin
Software Engineer at Google
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolShuning Jin is a software engineer in the San Francisco Bay Area with eight years of experience blending machine learning research and full-stack development, currently at Google after completing an MS in Computer Science at Rutgers. She has hands-on expertise in NLP and ML—evidenced by contributions to the popular jiant toolkit where she worked on preprocessing, model architecture, and training scripts—and a track record of published AI research from internships at TTIC and Johns Hopkins. Comfortable across Python, PyTorch, Java, and SQL, she builds scalable systems that bridge experimental models and production training pipelines. Known for tuning and automating model workflows, she brings a pragmatic researcher’s rigor to engineering problems at the intersection of software and language technologies.
8 years of coding experience
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Rutgers University–New BrunswickBachelor of Science (BS), Computer Science, Statistics, Bachelor of Science (BS), Computer Science, Statistics at University of Minnesota Duluth
Chinese, English
Github Skills (10)
data-preprocessing10
pytorch10
machine-learning10
nlp10
trainings10
python10
modeling10
transformers9
tensorflow7
bash7
Programming languages (2)
Github contributions (5)
nyu-mll/jiant
Jun 2018 - Jun 2019
jiant is an nlp toolkit
Role in this project:
Back-end Developer
Back-end DeveloperContributions:73 commits, 2 PRs, 5 pushes in 11 months
Contributions summary:Shuning primarily contributed to the `src/` directory, modifying files related to task processing, model building, and training. They made changes to core files such as `preprocess.py`, `tasks.py`, and `models.py`, indicating involvement in the data preprocessing pipeline, task definition, and model architecture. They also modified `trainer.py`, which points to working on the training logic. Furthermore, the user worked on bash scripts to tune the models, reflecting on the parameter tuning.
nlptransformersmultitask-learningsentence-representationbert
shuningjin/SemEval2018-Task2-EmojiDetection
Mar 2018 - Feb 2020
Contributions:15 commits, 13 pushes, 1 branch in 1 year 11 months
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