Puneet Ludu is a Machine Learning Engineer with 12 years of experience building production ML systems across consumer and financial data domains, currently helping Zillow migrate legacy valuation pipelines to containerized, scalable deployments. He holds an M.S. in Computer Science from SUNY Buffalo and has driven end-to-end ML work—from feature engineering and modeling to alerting and deployment—at OkCupid and FactSet, where he delivered projects like speaker identification, private company fact extraction, and real-time duplicate document detection. Comfortable across Python, Keras, Spark, Java and AWS, Puneet blends research rigor (multiple publications) with pragmatic engineering, having automated builds and packaging for open-source desktop tooling in his GitHub work. He has a track record of turning messy, large-scale data (1.6M crawled sites, streaming docs) into reliable ML products that materially impact revenue and operations.
12 years of coding experience
9 years of employment as a software developer
Bachelor of Technology (BTech), Computer Science and Engineering, Bachelor of Technology (BTech), Computer Science and Engineering at Jaypee Institute Of Information Technology
Master of Science (M.S.), Computer Science, Master of Science (M.S.), Computer Science at State University of New York at Buffalo
Contributions:6 releases, 5 reviews, 58 commits in 3 years
Contributions summary:Puneet primarily focused on automating the build and installation process for the Lotion application. Their commits involve modifications to `create_shortcut.sh`, `install.sh`, and `setup.sh` scripts, demonstrating a focus on creating desktop shortcuts and packaging the application. They also worked on the `uninstall.sh` script, indicating responsibility for the complete lifecycle of the application on the user's system. The user also made contributions related to web and native application build and deployment.
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