Naman Nandan
Software Development Engineer 2 at Amazon Web Services (AWS)
San Jose, California, United States
Summary
🤩
Rockstar🎓
Top SchoolNaman Nandan is a Software Development Engineer 2 with 11 years of experience building production-grade backend and infrastructure systems, currently focused on generative AI and model serving at AWS in San Jose. He contributes to TorchServe—an important open-source PyTorch model server—where his work on dropping Python 2 support, improving metrics/configuration, and addressing gRPC and model-versioning issues highlights a focus on operational efficiency and maintainability. At SageMaker he implemented sticky session routing for low-latency generative AI and helped enable resilient foundation-model training with the HyperPod operator, demonstrating expertise across inference and large-scale training workflows. His background spans systems firmware, networking automation, and SoC verification, giving him a rare blend of low-level systems and cloud-native engineering skills. Pragmatic and detail-oriented, he frequently turns operational pain points into durable, automated solutions that scale.
11 years of coding experience
4 years of employment as a software developer
Master's degree Electrical and Computer Engineering, Master's degree Electrical and Computer Engineering at Purdue University - Office of the Vice Provost for Graduate Students and Postdoctoral ScholarsBachelor of Engineering - BE Electronics and Communication Engineering, Bachelor of Engineering - BE Electronics and Communication Engineering at PES Institute of Technology
Github Skills (12)
docker10
python10
dockers10
cicd10
devops9
metric9
machine-learning9
pytorch9
kubernetes8
kubernetes-pods8
optimization8
grpc7
Programming languages (3)
Github contributions (5)
pytorch/serve
Nov 2022 - Jan 2023
Serve, optimize and scale PyTorch models in production
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:256 reviews, 8 commits, 115 PRs in 2 months
Contributions summary:Naman's contributions primarily focused on improving the TorchServe environment and its functionality. They dropped Python 2 support and removed dependencies on the `future` package, streamlining the code and updating environment information. Furthermore, the user added configuration options for disabling system metrics, integrated benchmarks, and addressed issues related to gRPC and model versioning. These changes highlight a focus on maintainability, operational efficiency, and improving performance.
cpupytorchpytorch-modelsservingin-production
namannandan/serve
Aug 2022 - Sep 2024
Serve, optimize and scale PyTorch models in production
Contributions:2 reviews, 4 PRs, 356 pushes in 2 years 1 month
pytorchpytorch-modelsin-productiondeep-learningtorch
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