Ishaan Malhi
Senior Research Engineer at Google DeepMind
Berkeley, California, United States
Summary
👤
Senior🎓
Top SchoolIshaan Malhi is a Senior Research Engineer at Google DeepMind with 11 years of experience building and deploying machine learning systems across industry and academia. He combines deep learning research (published work in radiology and robustness) with production ML engineering from roles at Apple (Siri search relevance) and infrastructure-first positions at Insider.in. A UC Berkeley MEng and Stanford-affiliated researcher, he mentors students and has built scalable ML infrastructure on Kubernetes for academic projects. Ishaan is also an active full-stack open-source contributor—refactoring and modularizing projects like Shoes 4 and adding features such as animations and streamlined styling. He brings a rare blend of hands-on software craftsmanship, research rigor, and product-focused deployment experience in AI for healthcare and search. Based in Berkeley, he is particularly skilled at translating novel research into robust, production-ready systems.
10 years of coding experience
6 years of employment as a software developer
Master of Engineering - MEng Electrical Engineering and Computer Sciences, Master of Engineering - MEng Electrical Engineering and Computer Sciences at University of California, BerkeleyKendriya Vidyalaya SangathanBachelor of Engineering (B.E.) Computer Engineering, Bachelor of Engineering (B.E.) Computer Engineering at University of MumbaiStanford University
English, Hindi
Github Skills (9)
refactoring10
windows-gui10
code-organization10
shoes10
ruby10
architecture9
jruby9
architectures9
cross-platform8
Programming languages (10)
Github contributions (5)
shoes/shoes4
Feb 2017 - Mar 2017
Shoes 4 : the next version of Shoes
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:13 commits, 7 PRs, 14 comments in 25 days
Contributions summary:Ishaan primarily refactored and restructured the Shoes 4 project, moving DSL text methods to the DSL::Text module and extracting interactions, art, element, media, and styling functionalities. These changes involved reorganizing the codebase into distinct modules and extracting relevant functionalities to improve code organization. The user also introduced features such as animations and extracted styling and setup methods to streamline the development process.
mac-osxwindowsswtnext-versionlinux
OrthoDex/ubuntu-node
Nov 2018 - Feb 2020
Production ready Node.js docker images based on Ubuntu.
Contributions:1 release, 8 commits, 1 branch in 1 year 2 months
containersdockerfiledocker-imagenode-jsproduction-ready
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