Pararth Shah
Founder at Stealth
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolPararth Shah is a founder and seasoned engineering leader with 14 years building large-scale conversational AI and agentic systems, most recently leading Gemini’s Agentic framework and a Google Assistant rebuild at Google before founding a stealth startup in 2024. He has led teams of 20–30 ML engineers and researchers at Google and Meta, shipping semantic parsing, grounding, state tracking and voice-assistant features across products and devices. A hands-on systems builder with roots in research, he contributed to Stanford’s SNAP graph library—optimizing core table-to-graph sequence operations—and was among the earliest hires at Sourcegraph. Based in the San Francisco Bay Area, he combines deep technical fluency, low-ego collaboration, and a taste for hard, meaningful problems that create wealth and joy for teams.
14 years of coding experience
11 years of employment as a software developer
Indian Institute of Technology BombayMaster of Science (MS) Computer Science, Master of Science (MS) Computer Science at Stanford University
Stackoverflow
8,114reputation
914kreached
294answers
6questions
android
top-1%
Github Skills (18)
graph-algorithms10
c-language10
data-structure10
android10
data-structures10
cprogramming-language10
permission9
performance-optimization9
computer-engineering9
bluetooth-low-energy9
android-location6
android-settings6
google-play-services6
android-bluetooth6
adapter6
Programming languages (3)
Github contributions (5)
snap-stanford/snap
Nov 2013 - Jun 2014
Stanford Network Analysis Platform (SNAP) is a general purpose network analysis and graph mining library.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:65 commits in 6 months
Contributions summary:Pararth's primary contributions involve significant modifications and enhancements to the `TTable` class within the SNAP library. These changes include the implementation and optimization of graph sequence functionalities, with the addition of `ToGraphSequence` and related methods to create graph sequences from tables. The user also refactored existing graph-related functions and improved the performance of fundamental operations like join and select. The user also made updates related to column naming.
stanfordpythonminingpurposegraph
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