Manvenddra Rawat is a Staff Engineer with a focus on AI model efficiency and scalable MLOps, bringing around 3 years of concentrated experience at Qualcomm and prior infrastructure automation roles at Cognizant. He has led teams of 8–12 engineers to deliver production-grade solutions—from model quantization and autonomous driving integrations to automated verification pipelines that reduce manual overhead. Technically adept in Python, TensorFlow, Docker, cloud integrations, and model quantization, he pairs hands-on implementation (e.g., automated Gerrit/Jenkins tooling and bisect-driven regression detection) with a systems-level view of deployment reliability. His background in AIOps, anomaly detection, and ML-based RCA chatbots reflects a rare blend of infrastructure engineering and applied ML. Recognized with Qualcomm Impact and Orion awards, he emphasizes measurable outcomes: faster deployment, higher model accuracy, and streamlined operations. Curious and collaborative, he’s now focused on generative models and making scalable AI solutions more accessible.
3 years of coding experience
9 years of employment as a software developer
12th (ISC) Science, 12th (ISC) Science at Pine Hall School
Bachelor of Technology (BTech) Computer Science, Bachelor of Technology (BTech) Computer Science at Uttrakhand Technical University, Dehradun
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
Contributions:2 reviews, 19 commits, 38 PRs in 5 months
pytorchtechniquesdeep-learningpruningcompression
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