Jeetendra Patil
Senior DevOps Engineer at Adobe
Fremont, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJeetendra Patil is a Systems Development Engineer II with 10 years of experience building and automating cloud-native infrastructure for AI and ML at scale. Based in Fremont, CA, he designs CI/CD pipelines, build-and-release systems, and test infrastructures for AWS Deep Learning Containers and DLAMI, blending deep Docker, Python, and Linux expertise. At AWS he helped operationalize training and inference images for TensorFlow, PyTorch and other frameworks, contributing directly to the build/test tooling of a widely used AWS open-source container project. Prior roles in SRE and test engineering sharpened his focus on reliability, automation, and developer productivity across the full lifecycle. He holds advanced computer science degrees and quietly excels at turning complex integration problems into reproducible, automated workflows.
11 years of coding experience
14 years of employment as a software developer
Master of Science (M.S.) Computer Science, Master of Science (M.S.) Computer Science at The University of Texas at ArlingtonBachelor of Engineering (B.E.) Computer Science, Bachelor of Engineering (B.E.) Computer Science at Walchand College of Engineering, Sangli, India
Github Skills (14)
build-time10
build-engine10
build210
buildx10
cicd10
testing10
dockers9
pytest9
python9
sagemaker9
aws9
docker9
tensorflow7
pytorch7
Programming languages (4)
Github contributions (5)
aws/deep-learning-containers
Apr 2021 - Nov 2022
One stop shop for running AI/ML on AWS.
Role in this project:
DevOps Engineer
DevOps EngineerContributions:336 reviews, 47 commits, 188 PRs in 1 year 7 months
Contributions summary:Jeetendra primarily contributed to the build and test infrastructure, as evidenced by changes to Dockerfiles, test scripts, and configuration files. Their work included adding and updating license attributions, integrating EFA configurations for testing, and updating package versions. The user also made changes to testing frameworks (pytest) and Sagemaker test configurations.
aiawsmachine-learningml
jeet4320/deep-learning-containers
Feb 2021 - Jul 2025
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.
Contributions:587 pushes, 160 branches in 4 years 5 months
caffe2trainingtensorflowawsserving
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