Jeni Shah
Software Engineer at Google
Bengaluru, Karnataka, India
Summary
👤
Senior🎓
Top SchoolJeni Shah is a Machine Learning Engineer with 11 years of experience, currently at Google after leading ML efforts at Freshworks and FactSet. She holds an M.Tech in Machine Learning and builds end-to-end ML pipelines with deep expertise in NLP and practical computer vision experience. Jeni has contributed to the widely used Gensim library—optimizing its Phrases module, improving documentation, and fixing corpus and visualization issues—demonstrating attention to scalable NLP tooling. Based in Bengaluru, she blends research-grade knowledge with production-focused engineering, routinely shipping memory-optimized, well-documented solutions that bridge prototypes to reliable services.
11 years of coding experience
6 years of employment as a software developer
Bachelor of Engineering (B.E.) Electronics and Communication Engineering, Bachelor of Engineering (B.E.) Electronics and Communication Engineering at L.D. College of EngineeringMaster of Technology - MTech Machine Learning, Master of Technology - MTech Machine Learning at Dhirubhai Ambani Institute of Information and Communication Technology
Hindi, English, Gujarati
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (8)
gensim10
topic-modeling10
topic-models10
python10
natural-language-processing10
machine-learning9
plotly7
data-mining7
Programming languages (4)
Github contributions (5)
piskvorky/gensim
Oct 2018 - Aug 2020
Topic Modelling for Humans
Role in this project:
Data Scientist
Data ScientistContributions:5 commits, 4 PRs, 9 comments in 1 year 10 months
Contributions summary:Jeni primarily contributed to the Gensim library, focusing on improvements related to the `Phrases` module, including documentation updates for scoring functions and memory optimization. They addressed an incompatibility issue with `plotly` for visualizations and fixed an `AttributeError` in the `WikiCorpus` class. Their work demonstrates a focus on refining core functionalities, improving documentation, and optimizing the library's performance.
pythonword-similarityword-embeddingsdata-miningfor-humans
jenishah/gensim
Sep 2018 - Aug 2020
Topic Modelling for Humans
Contributions:18 pushes, 6 branches in 1 year 11 months
nlpjavascriptmachine-learningfor-humanstopic-modelling
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