Snehit Vaddi is an AI Data Engineer with 8 years of experience building HIPAA-compliant, production-grade data and AI systems that scale—most recently architecting ModMed’s AI Scribe to process 500M+ patient conversations in real time and deliver a 206% ROI across 40K+ providers. He combines a master’s in computer science from the University of Florida with hands-on research (vision transformers for hyperspectral contamination detection) and production MLOps, having accelerated deployment cycles 16× for large agricultural imagery pipelines. Past roles include optimizing big-data NLP at AT&T to save $2M annually and designing RAG/GenAI ingestion pipelines for low-latency search at GeoSpider. Equally at home in SQL/NoSQL and CV/ML stacks, he focuses on practical systems that let clinicians speak naturally to AI while keeping privacy and reliability front and center. Outside work he contributes to open source, organizes tech events, and runs BuyMLProject.com to help teams jumpstart ML projects.
8 years of coding experience
2 years of employment as a software developer
Bachelor of Technology - BTech Computer Science, Bachelor of Technology - BTech Computer Science at GITAM Deemed University
Master's degree Computer Science, Master's degree Computer Science at University of Florida
This Repo consists of implementing First order motion model for making Deep Fakes. It is referenced from a video on youtube by Two Minute Papers about Deep Fakes. The code given by @AliaksandrSiarohin
Contributions:26 commits, 14 PRs, 26 pushes in 2 years 3 months
Project on getting the angle of steering rotation in a self-driving car. This project is inspired by NVIDIA End to End Learning for Self-Driving Cars and data is gathered from Udacity's Behavioral Cloning repository.
Contributions:60 commits, 56 pushes, 1 branch in 2 years 2 months
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