Karan Shukla

Software Engineer at Google

San Francisco, California, United States
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Summary

👤
Senior
🎓
Top School
Karan Shukla is a software engineer with a decade of experience building AI tooling, transparency, and infrastructure for top tech companies across San Francisco. He has led Model Transparency Tooling at Google and drove system-level AI transparency and provenance efforts at Meta, shipping AI System Cards across 20+ product surfaces and prototyping C2PA provenance ingestion that influenced company-wide commitments. Comfortable across Python and JavaScript, Karan contributes to open-source ML interpretability work such as TensorFlow's TCAV, where he added proto-formatted outputs and Relative TCAV support. Currently focused on Chrome AI memory, context, and personalization, he pairs technical leadership with cross-functional execution—bridging product, UX, internationalization, and policy to operationalize responsible AI.
code10 years of coding experience
job4 years of employment as a software developer
bookBachelor of Science (B.S.) Computer Science, Bachelor of Science (B.S.) Computer Science at The University of Texas at Dallas
languagesEnglish
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Stackoverflow

Stats
1,023reputation
40kreached
5answers
36questions
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Github Skills (12)

machine-learning10
interpretation10
tensorflow10
python10
protobuffer10
protobuf10
gensim6
docker6
scipy6
try-catch6
unicode6
numpy6

Programming languages (4)

JavaRustJupyter NotebookPython

Github contributions (5)

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tensorflow/tcav

Jul 2019 - Aug 2019

Code for the TCAV ML interpretability project
Role in this project:
userML Engineer
Contributions:15 commits, 9 PRs, 11 comments in 1 month
Contributions summary:Karan implemented features related to TCAV (Testing with Concept Activation Vectors) interpretability project. They modified the codebase to return TCAV results in a proto format, adding a new `return_proto` argument to the `TCAV.run()` method and modifying several files, including `utils.py`, `tcav.py`, and `results.proto`, and added the `target_class` int. In addition, they updated the `results.proto` to include CAVaccuracies. Furthermore, they added support for Relative TCAV.
pytorchtcavnlpinterpretabilitydeep-learning
shuklak13/shuklak13

Aug 2016 - Jul 2022

Contributions:27 pushes, 1 branch in 5 years 11 months
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Karan Shukla - Software Engineer at Google