Sattvik Sahai is an Applied Scientist II at Amazon’s AGI team in San Jose with nine years of experience building ML and AI systems, currently focused on large language models for code at the intersection of cybersecurity and AI safety. He progressed through roles at Amazon from SDE to applied scientist, bringing production-grade engineering discipline to research problems. His background includes ML research and applied R&D across Honeywell and KLA, shipping models for visual odometry, anti-spoofing, activity classification, and label-noise detection. A Stevens Institute of Technology MS in Machine Learning and prior teaching experience in deep learning and data structures underline his strong academic and mentorship instincts. Colleagues describe him as someone who bridges low-level system constraints and cutting-edge ML, able to move prototypes into robust deployment pipelines. Based in the Bay Area, he blends curiosity about safe AI with hands-on experience securing and scaling models used in safety-critical domains.
8 years of coding experience
7 years of employment as a software developer
Bachelor of Technology Electronics and Communications Engineering, Bachelor of Technology Electronics and Communications Engineering at Manipal Institute of Technology
Master of Science Machine Learning, Master of Science Machine Learning at Stevens Institute of Technology
A python library to simulate Collaborative Deep Learning. It provides the flexibility to simulate various network architectures, Collaborative Learning Stratergies, and privacy invasion attacks. Currently built for Pytorch, this library is a work in progress.
Contributions:25 commits, 21 pushes, 2 branches in 3 months
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Sattvik Sahai - Applied Scientist II, AGI at Amazon