Gaurav Ghati
Software Development Engineer at Amazon Web Services (AWS)
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolGaurav Ghati is a Software Development Engineer at AWS Redshift with seven years of experience building scalable backend systems, distributed services, and cloud-native architectures. He has driven cost-saving, serverless solutions at AWS—building a Redshift Self Usage Dashboard that cut US-East-1 operational spend by roughly $650K/month—and has solid experience with Lambda, CloudFormation, DynamoDB, and cross-account IAM. Earlier roles include improving CI/CD and Java service reliability at BNY for a 60,000+ user e-signature platform and research work applying Bi-LSTM and BERT for document matching and incremental learning. An avid open-source contributor, he’s implemented and tested LSTM and other layers in the high-performance C++ mlpack machine learning library, reflecting a strong ML systems bent. He holds a Master of Computer Science from UC Irvine (3.8+ GPA) and a high-performing academic background from Pune Institute of Computer Technology. Known for “Think twice, code once,” he blends careful engineering with practical production impact.
7 years of coding experience
2 years of employment as a software developer
Bachelor of Engineering, Information Technology, GPA : 9.21 / 10, Bachelor of Engineering, Information Technology, GPA : 9.21 / 10 at Pune Institute of Computer TechnologyKendriya Vidyalaya SangathanUniversity of California, Irvine
Github Skills (14)
deeplearning-ai10
lstm10
machine-learning10
deep-learning10
cpp10
cplus10
testing9
algorithms8
data-structures8
algorithm8
data-structure8
regression4
nearest-neighbor-search3
nearest-neighbors3
Programming languages (8)
Github contributions (5)
mlpack/mlpack
Dec 2020 - Dec 2020
mlpack: a fast, header-only C++ machine learning library
Role in this project:
ML Engineer
ML EngineerContributions:4 reviews, 8 commits, 3 PRs in 16 days
Contributions summary:Gaurav primarily contributed to the implementation and testing of machine learning-related components, specifically focusing on the Long Short-Term Memory (LSTM) layer within the mlpack library. They added copy and move constructors, assignment operators, and weight size calculations for the LSTM layer. Additionally, the user incorporated test cases to verify the functionality of the LSTM layer. They also introduced tests for other layers, such as transposed convolution and noisy linear layers.
regressionheaderdeep-learningscientific-computingc-plus-plus
nmd2611/NCC-2020
Feb 2020 - Apr 2020
Contributions:50 commits in 2 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.