Jackie
Summary
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SeniorJacqueline Xu is a product manager and MIT-trained AI engineer with 11 years of experience building ML-driven safety and civic impact products at Meta and Threads. She led and shipped machine-learning improvements that measurably reduced misinformation and scaled detection of abusive civic content, and earlier contributed novel feature layers to the widely used Caffe2 deep learning framework. Comfortable bridging research and product, she taught AI and led startup labs at MIT while publishing thesis work on meta-learning for personalized affect estimation. Based in New York, Jacqueline combines technical depth in model development with cross-functional leadership in trust & safety and social impact. She is as comfortable mentoring students and running demos as she is iterating on production ranking systems that affect millions.
11 years of coding experience
Github Skills (8)
machine-learning10
artificial-intelligence10
caffe10
deep-learning10
python10
ml10
numpy9
unit-testing9
Programming languages (4)
Github contributions (5)
facebookarchive/caffe2
Jun 2017 - Aug 2017
Caffe2 is a lightweight, modular, and scalable deep learning framework.
Role in this project:
ML Engineer
ML EngineerContributions:22 commits in 1 month
Contributions summary:Jackie primarily contributed to the development and implementation of machine learning layers within the Caffe2 deep learning framework. Their work involved creating and integrating new layers such as Dropout, Random Fourier Features, Semi-Random Features and Arc Cosine feature map, and incorporating them into the existing model and training pipelines. The user also wrote unit tests to ensure the correct functionality of these new layers. This work enhances the framework's capabilities for various deep learning tasks by expanding the types of layers available for model building.
caffedeep-learningmachine-learningaiartificial-intelligence
jackielxu/settings
Jan 2016 - Apr 2017
Contributions:5 pushes, 1 branch in 1 year 3 months
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