Aniruddha Patil
Software Development Engineer at Amazon Web Services (AWS)
Vancouver, British Columbia, Canada
Summary
👤
Senior🎓
Top SchoolAniruddha Patil is a software development engineer with a decade of engineering experience and 4+ years focused on shipping large-scale cloud services at AWS, where he drives feature work and reliability for AWS Metering using Java, EMR, Lambda and CDK. He pairs production-grade backend expertise with a history of building user-facing systems—from a virtual campus tour that attracted 20,000 weekly users to React/Node progressive web apps and mobile launches. His background spans machine learning and computer vision research (TensorFlow Lite, synthetic data generation) as well as hands-on internships that resulted in published work and app store products. Currently based in Vancouver while completing an MS in Computer Science at Indiana University, he blends academic rigor (3.81 GPA) with operational on-call experience handling sev2 incidents. Notably comfortable across cloud-native infrastructure, data pipelines, and full-stack development, he brings both product intuition and a track record of scaling real-world systems.
10 years of coding experience
2 years of employment as a software developer
Master of Science - MS, Computer Science, 3.81, Master of Science - MS, Computer Science, 3.81 at Indiana University BloomingtonBachelor of Technology, Computer Science, 7.59, Bachelor of Technology, Computer Science, 7.59 at International Institute of Information Technology
English, Hindi, Marathi
Github Skills (39)
svm-classifier9
knn-classification9
weather-data8
react8
discovery8
gaussian-mixture-models8
file-transfer6
data-gateway6
music5
random-forest5
gateway5
apache5
java5
classification5
pdf4
Programming languages (5)
Github contributions (5)
forksociety/AhaEvent
May 2020 - May 2020
A tech conference discovery platform
Contributions:1 review, 83 commits, 15 PRs in 13 days
eventsreactdiscoverydiscovery-platformopensource-events
aniruddhavpatil/MusicGenreClassification
Nov 2017 - Dec 2019
Statistical Methods in Artificial Intelligence course project on implementing the paper Music Genre Classification by Haggblade et al (http://cs229.stanford.edu/proj2011/HaggbladeHongKao-MusicGenreClassification.pdf)
Contributions:6 commits, 2 pushes in 2 years
genre-classificationkmeans-clusteringmel-frequency-cepstral-coefficientsclassificationpdf
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