Sanket Lokegaonkar
Senior Applied Scientist at Amazon
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolSanket Lokegaonkar is a Senior Applied Scientist at Amazon with a decade of experience building large-scale ML systems and production infrastructure, and was a founding member of the pre-training data team for Amazon Rufus that serves hundreds of millions of customers. He co-led data strategy, training recipes, and curriculum design across 5+ model generations, and previously built DataKit for distributed dataset management and checkpointing. His background spans research and engineering in LLMs, data-centric ML, scaling laws, representation learning, and agentic mid-training, with publications at ICLR, NAACL, EMNLP and SIGGRAPH. Before Amazon he shipped ML-driven features for autonomous vehicles at Uber and scalable compliance services at AWS, and earlier work includes real-time distributed analytics at Bloomberg and continual learning research at Virginia Tech. Based in Seattle, he blends deep research chops with production engineering rigor and a knack for practical dataset tooling that accelerates model iteration.
10 years of coding experience
9 years of employment as a software developer
SSC, SSC at St.Pauls High School,DadarMaster of Science (M.S.), Computer Science, Master of Science (M.S.), Computer Science at Virginia TechBachelor of Engineering (BE), Computer Engineering, Bachelor of Engineering (BE), Computer Engineering at University of Mumbai
English, Hindi, Marathi
Github Skills (19)
python10
data-science10
machine-learning10
deep-learning10
tensorflow10
neural-network10
ml9
deep-neural-networks9
action-recognition7
computer-vision5
matrix2
scikit1
kubernetes1
race-detection1
data-race1
Programming languages (3)
Github contributions (5)
sanketloke/sanketloke.github.io
May 2017 - Apr 2019
Personal blog powered by Jekyll
Contributions:4 PRs, 23 pushes, 1 branch in 1 year 11 months
jekylljekyll-theme
sanketloke/pytorch-fcn
Jan 2018 - Jan 2018
Contributions:24 pushes in 3 days
pytorchdeep-learningconvolutionalconvolutional-networksfully-convolutional-networks
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