Namrata Madan
Senior Software Development Engineer at Amazon Web Services (AWS)
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolNamrata Madan is a Senior Software Development Engineer at AWS SageMaker with a decade of experience building backend systems and ML-focused tooling. She has worked across SageMaker features—experiments tracking, Studio Search, pipelines, and StudioLab—shipping operational improvements that reduce friction for model training and deployment. Her open-source contributions to the widely used aws/sagemaker-python-sdk show hands-on expertise in pipeline orchestration, caching fixes, and resolving resource conflicts to make ML workflows more reliable. Prior roles at Amazon include optimizing content management for Prime marketing and building internal tools, reflecting a blend of customer-facing and developer productivity work. Based in Seattle and grounded in a Computer Engineering degree from Purdue, she pairs deep backend engineering skills with practical ML infrastructure experience.
10 years of coding experience
4 years of employment as a software developer
Bachelor's Degree Computer Engineering, Bachelor's Degree Computer Engineering at Purdue University
English, Hindi
Github Skills (12)
machine-learning10
workflow-management10
aws10
python10
pipeline10
sagemaker10
testing9
tensorflow8
pytorch8
huggingface7
docker6
dockers6
Programming languages (2)
Github contributions (5)
aws/sagemaker-python-sdk
Mar 2021 - Oct 2022
A library for training and deploying machine learning models on Amazon SageMaker
Role in this project:
ML Engineer
ML EngineerContributions:58 reviews, 13 commits, 12 PRs in 1 year 7 months
Contributions summary:Namrata contributed to the `aws/sagemaker-python-sdk` repository, focusing on enhancements to the SageMaker workflow functionality. Their work involved modifying training step parameters, updating lambda code for pipeline operations, and addressing caching issues. The user also worked on fixing resource conflicts and implementing a helper method for generating pipeline adjacency lists, indicating a strong focus on improving the pipeline's operational aspects within the SageMaker environment.
pytorchsagemakerdeployingmxnetpython
nmadan/sagemaker-python-sdk
Mar 2021 - Aug 2022
A library for training and deploying machine learning models on Amazon SageMaker
Contributions:43 pushes, 1 branch in 1 year 5 months
deployingsagemakeramazon-sagemakerdeploying-machine-learningamazon
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