Tanaya Babtiwale
Machine Learning Engineer 3 at Adobe
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolTanaya Babtiwale is a Machine Learning Engineer with a decade of experience focused on conversational AI, NLP, and deep learning, currently advancing language technology at Adobe in the San Francisco Bay Area. She has built production dialogue systems and multilingual NER, optimized automation for millions of daily queries at Haptik, and enhanced semantic search and long-query handling with knowledge-graph approaches at Adobe. A University of Washington computational linguistics MS graduate, she bridges linguistic insight and engineering rigor—evident from an NLIDB research project published at COLING and hands-on open-source work improving multilingual entity recognition for chatbots. As a founder and community leader (Women X Code, Women Who Code), she pairs product-minded engineering with mentorship and ecosystem-building. Notably, she combines research-grade semantic representations with pragmatic production deployments, making complex dialogue and personalization problems operational at scale.
9 years of coding experience
10 years of employment as a software developer
Master of Science - MS, Computational Lingustics, Master of Science - MS, Computational Lingustics at University of WashingtonBachelor of Technology - BTech, Computer Science, Bachelor of Technology - BTech, Computer Science at SVKM's Narsee Monjee Institute of Management Studies (NMIMS)Linguistics, Linguistics at University of Mumbai
Github Skills (4)
natural-language-processing10
python10
nlpjs9
nlp9
Programming languages (1)
Github contributions (5)
hellohaptik/chatbot_ner
Jun 2021 - Jul 2022
chatbot_ner: Named Entity Recognition for chatbots.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:27 reviews, 67 commits, 30 PRs in 1 year 1 month
Contributions summary:Tanaya primarily focused on modifying and refactoring language constants within the `chatbot_ner` repository. Their commits involved adding and removing variations related to "name" in different languages, likely for named entity recognition purposes. They also addressed linting errors and optimized the code by sorting previous message variations by length. The user's contributions centered on improving the accuracy and efficiency of the named entity recognition system for chatbots.
nlpchatbotsnamed-entity-recognitionnerentity-recognition
tanaya-b/tanaya-b.github.io
Apr 2020 - Nov 2022
Contributions:12 pushes, 1 branch in 2 years 7 months
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