Anagha Kulkarni is a Senior Applied ML Scientist with 11 years of experience building production-grade NLP and ML systems, currently based in Seattle. She holds a Ph.D. in Computer Science from Arizona State University and has applied her research background to develop end-to-end inference APIs, context-aware BERT variants, LayoutLM and relation-extraction models, and semantic search pipelines at companies like Invitae and Rokt. Her work spans prototyping to deployment, including custom token strategies, Hugging Face and PyTorch implementations, FAISS and NMSLib indexing, and internal tooling for named entity and relation extraction. She has industrial ML experience from internships at Instagram and PARC and a track record of translating academic research into practical, scalable solutions. Known for combining deep NLP expertise with pragmatic engineering, she recently transitioned into senior applied roles at Rokt and JPMorgan Chase, signaling a focus on delivering ML systems at enterprise scale.
11 years of coding experience
10 years of employment as a software developer
Master of Science (MS) Computer Science, Master of Science (MS) Computer Science at University of Southern California
Bachelor of Engineering (BEng) Computer Science, Bachelor of Engineering (BEng) Computer Science at Gogte Institute of Technology
Doctor of Philosophy (PhD) Computer Science, Doctor of Philosophy (PhD) Computer Science at Ira A. Fulton Schools of Engineering at Arizona State University
Contributions:2 PRs, 5 pushes, 1 branch in 1 year 4 months
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Anagha Kulkarni - Senior Applied ML Scientist at JPMorganChase