Ansh Babbar
Senior Analyst at PwC
New Delhi, Delhi, India
Summary
🤩
Rockstar🎓
Top SchoolAnsh Babbar is a self-taught software engineer and founder with four years of experience building AI-first products and early-stage startups from 0 to 1. He currently splits time between founding Strift, an AI-powered fashion discovery engine, and senior analyst work at PwC, after helping launch klaro.care — an AI health-tech prototype addressing Germany’s nursing shortage. Hands-on across product, backend C++ contributions (including code quality and tests to the mlpack machine learning library), and mobile/web stacks, he blends engineering with product design and GTM instincts. Comfortable in accelerator environments and cross-functional roles, he leverages tools from OpenAI integrations to Flutter and MemGPT to ship scalable prototypes. Notably, his open-source focus on reliability (formatting, tests, docs) reflects a pragmatic commitment to maintainable ML systems.
4 years of coding experience
1 year of employment as a software developer
Bachelor of Technology Computer Science Engineering Artificial Intelligence, Bachelor of Technology Computer Science Engineering Artificial Intelligence at Bennett University10+2 Science with Computer Science CBSE, 10+2 Science with Computer Science CBSE at Summer Fields School
English, Hindi, French
Github Skills (7)
regression10
machine-learning10
logistic-regression10
cpp10
random-forest10
cplus10
testing9
Programming languages (6)
Github contributions (5)
mlpack/mlpack
Oct 2023 - Dec 2023
mlpack: a fast, header-only C++ machine learning library
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 reviews, 1 PR, 10 comments in 1 month
Contributions summary:Ansh primarily contributed to the mlpack project by fixing code formatting issues, such as extra spaces and indentation. Their work included modifying existing code within the logistic regression and random forest modules of the library. Further contributions involved updating documentation examples and adding tests for the logistic regression model, specifically checking for training accuracy. These commits demonstrate a focus on code quality and improving the usability of the library.
regressionheaderdeep-learningscientific-computingc-plus-plus
rabbabansh/AuctionBlockchain
Jun 2021 - Oct 2023
Contributions:4 pushes, 1 branch in 2 years 4 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.