Kate Swift-spong
Software Engineer - Machine Learning at Meta
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolKate Swift-spong is a software engineer specializing in machine learning with nine years of experience building data-driven products that improve user experiences, currently at Meta in San Francisco. She brings a strong research background in human-robot interaction from a Ph.D. at USC, where she designed experiments, deployed autonomous robots, and achieved a notable 98% adherence to robot reminders in longitudinal studies. At Intuit she translated research-grade analytics into production-ready models and at Insight Data Science she shipped an AWS-deployed Flask app that combined CNN transfer learning with web-scraped datasets. Comfortable across Python, R, and Linux environments, her toolkit spans classical ML, deep learning, and robust data engineering with practical visualization and experimental-design chops. Unusually for an ML engineer, she pairs production model work with hands-on UX research and mentoring experience across high school to master’s students, bridging human-centered design and scalable systems.
9 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at University of Southern CaliforniaBachelor's degree Electrical and Computer Engineering, Bachelor's degree Electrical and Computer Engineering at Franklin W. Olin College of Engineering
Github Skills (8)
face8
robot8
tablet7
robot-control7
synchronized6
speech6
javascript5
speech-recognition4
Programming languages (1)
Github contributions (2)
interaction-lab/cordial-public
Mar 2017 - Oct 2018
Robot control for speech and synchronized behaviors, phone-based javascript face, and tablet interaface.
Contributions:9 commits, 2 PRs, 5 pushes in 1 year 7 months
behaviorsphonetabletjavascriptsynchronized
mishingo/strike-back
Feb 2018 - Feb 2018
Contributions:3 PRs, 4 pushes, 2 branches in 1 day
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