Rostam Vakhshoori
Software Engineer at Google
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolRostam Vakhshoori is a software engineer based in New York with six years of experience spanning machine learning, web development, and full-stack systems. Currently at Google, he brings practical ML and product-focused engineering from prior roles at Amazon and UC Irvine’s nonprofit-focused dev team. His open-source contributions include significant work on the Libra ergonomic ML framework—building image preprocessing pipelines and a CNN architecture that underscore his computer vision and data-prep strengths. He enjoys turning patterns in data into impactful software, and has a track record of simplifying model training and deployment for broader audiences. Colleagues describe him as an engineer who blends research-minded curiosity (he has mentored AI workshops) with pragmatic delivery in production environments.
7 years of coding experience
2 years of employment as a software developer
Leland High SchoolUniversity of California, Irvine
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (13)
image-preprocessing10
neural-network10
mask-rcnn10
faster-rcnn10
computer-vision10
machine-learning10
python10
data-science9
keras9
pandas8
automl8
scikit-learn6
scikit6
Programming languages (4)
Github contributions (5)
Palashio/libra
Jun 2020 - Jul 2020
Ergonomic machine learning for everyone.
Role in this project:
ML Engineer & Data Scientist
ML Engineer & Data ScientistContributions:31 commits, 12 PRs, 45 pushes in 1 month
Contributions summary:Rostam contributed significantly to the `libra` repository, an ergonomic machine learning framework. Their work focused on image preprocessing, including creating functions for setwise, csvwise, and classwise image data preparation, handling resizing, and creating training/testing sets. Furthermore, the user implemented a convolutional neural network (CNN) architecture, demonstrating expertise in computer vision and deep learning model development, including grayscale image support. They also addressed code structure, and improved robustness of the preprocessing steps.
machine-learningneural-networksauto-ml
ctc-uci/authentication-frontend
Dec 2021 - Feb 2022
Contributions:23 reviews, 6 PRs, 7 pushes in 1 month
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