Phoebe Mulcaire
Machine Learning Engineer at Duolingo
Pittsburgh, Pennsylvania, United States
Summary
👤
Senior🎓
Top SchoolPhoebe Mulcaire is a machine learning engineer specializing in multilingual and low-resource natural language processing, currently applying her research expertise at Duolingo. With a PhD from the University of Washington and a decade of experience, she focuses on language-agnostic methods and continuous token representations that enable semantic transfer from high-resource to low-resource languages. Her work blends deep research—such as vector quantization and vocabulary alignment projects during a Facebook AI internship—with production-minded engineering to improve real-world language learning systems. Based in Pittsburgh and grounded in a strong CS and cognitive science background from UC Berkeley, she brings both theoretical rigor and practical impact to cross-lingual representation challenges. An underappreciated strength is her persistent emphasis on subword and token-level techniques that quietly amplify multilingual model performance across many low-resource scenarios.
10 years of coding experience
Bachelor of Arts - BA, Computer Science and Cognitive Science, 3.98, Bachelor of Arts - BA, Computer Science and Cognitive Science, 3.98 at University of California, BerkeleyDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Washington
Github Skills (5)
allennlp6
dynet5
language-model5
pytorch3
neural-network2
Programming languages (2)
Github contributions (5)
pmulcaire/allennlp
Oct 2017 - Jun 2018
Contributions:49 pushes, 5 branches in 7 months
pytorchnlpbertdeep-learningmachine-learning
pmulcaire/rosita
Mar 2019 - Mar 2019
A fork of allenai/allennlp (and allenai/bilm-tf) for multilingual contextual representations
Contributions:12 commits, 5 pushes, 2 branches in 11 days
allennlp
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