Tanay Gahlot is a software engineer with 12 years’ experience building scalable, production-grade systems and ML-driven products across Google, Amazon, and startups. At Google he led teams that dramatically improved aspect extraction recall for Search and launched revenue-driving online bandit and auction-based reward optimization for Google Pay India. Earlier roles include designing an O(n) tax-reporting engine at Amazon and leading NLP/semantic tooling and semi-supervised biomarker work at Innoplexus. He contributes to scientific open-source (MNE-Python) improving dataset handling and cross-version compatibility, reflecting attention to reproducibility and data ergonomics. Based in Zurich, Tanay blends hands-on algorithmic optimization with product-focused infrastructure design and a founder’s pragmatic sense for when to pivot.
12 years of coding experience
5 years of employment as a software developer
Nanodegree, Artificial Intelligence, Nanodegree, Artificial Intelligence at Udacity
Bachelor of Technology (B.Tech.), Computer Science, 8.59/10, Bachelor of Technology (B.Tech.), Computer Science, 8.59/10 at National Institute Of Technology, Goa
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
Role in this project:
Data Scientist
Contributions:8 commits, 1 PR, 17 comments in 3 months
Contributions summary:Tanay primarily focused on modifying data loading and handling within the MNE-python library, specifically concerning the downloading and location of sample datasets. They updated URLs, resolved path issues, and ensured compatibility across different Python versions. Their work involved directory creation and management for storing and accessing data, contributing to the overall usability and accessibility of the datasets within the MNE framework.
Contributions:48 commits, 40 pushes, 3 branches in 3 years
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