Jagadish Krishnamoorthy
Senior Member Of Technical Staff , GPU Cloud WebApp Backend Development, Machine Learning Engineer at AMD
San Ramon, California, United States
Summary
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Senior🎓
Top SchoolJagadish Krishnamoorthy is a Senior Member of Technical Staff with 10+ years building GPU-cloud backend systems and ML infrastructure, currently designing scalable Python/Django APIs, Kubernetes deployments, and multi-node PyTorch training pipelines at AMD. He combines deep embedded-systems roots from Samsung and Intel with production cloud experience—EC2, S3, Redis, Celery, Slurm—and practical ops tooling (Ansible, Jenkins, Nginx) to bridge hardware-accelerated ML workloads to reliable web services. An active open-source contributor to PyTorch and other projects, he focuses on testing and cross-platform reliability for CUDA and ROCm, ensuring distributed training works across diverse hardware. Based in San Ramon, he brings uncommon breadth—from low-level firmware and protocol tooling to high-performance distributed ML systems—making him effective at debugging complex interactions between software, drivers, and GPU clusters.
10 years of coding experience
10 years of employment as a software developer
Master of Science (MS), Embedded System, Master of Science (MS), Embedded System at MCIS, ManipalKLEThe New Cambridge High School, BangaloreBachelor of Engineering (BE), Electrical and Electronics Engineering, Bachelor of Engineering (BE), Electrical and Electronics Engineering at Global Academy of Technology
Github Skills (14)
cuda10
pytorch10
roc10
gpu10
python10
distributed-computing10
testing10
machine-learning9
tensor9
deep-learning8
deeplearning-ai8
neural-network8
autograd8
numpy7
Programming languages (11)
Github contributions (5)
pytorch/pytorch
Nov 2020 - Jan 2023
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:10 reviews, 46 commits, 36 PRs in 2 years 2 months
Contributions summary:Jagadish primarily contributed to the testing infrastructure of the PyTorch project. Their work involved enabling and updating various tests, including those related to ROCm, distributed computing, and profiling tools. They fixed test failures, added new test cases, and increased memory requirements for existing tests, specifically targeting features and functionalities related to CUDA and ROCm. These changes indicate a focus on ensuring the reliability and performance of PyTorch across different hardware configurations and software environments.
pythongpu-accelerationdeep-learninggpunumpy
jaglinux/python-projects
Mar 2021 - Feb 2023
Contributions:47 commits, 45 pushes, 1 branch in 1 year 10 months
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