Young Park
Summary
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RockstarYoung Park is a software engineer with nine years of experience building cloud-native services and SDKs for Azure Machine Learning at Microsoft, based in Palo Alto. He blends backend engineering with ML deployment expertise, having modernized build and deployment pipelines to support bare Windows GPU VMs, conda environments, Azure Container Instances, and App Service. His open-source contributions to the high-profile microsoft/computervision-recipes repo show a focus on productionizing computer vision workloads and adapting infrastructure for Azure ML environments and CORS-aware web deployments. Stanford-educated and practiced at the intersection of DevOps and ML engineering, he brings a pragmatic, platform-first approach to shipping scalable, reproducible ML services.
9 years of coding experience
Github Skills (18)
python10
conda10
microsoft-azure10
azure-machine-learning10
cicd10
mlops10
azure10
devops10
kubernetes9
dockers9
machine-learning9
docker9
kubernetes-pods9
azure-app-service9
computer-vision9
Programming languages (4)
Github contributions (5)
microsoft/computervision-recipes
Jan 2020 - Oct 2020
Best Practices, code samples, and documentation for Computer Vision.
Role in this project:
DevOps Engineer & ML Engineer
DevOps Engineer & ML EngineerContributions:2 reviews, 15 commits, 32 PRs in 8 months
Contributions summary:Young's contributions primarily focused on infrastructure and deployment aspects within the computer vision project. They updated the build process and deployment for Azure DevOps pipelines by implementing changes for bare Windows GPU VMs and conda environment initialization. Furthermore, they made significant changes to deployment notebooks for Azure Container Instances (ACI) and Azure App Service, leveraging AzureML environments, and configuring CORS policies. The user demonstrates expertise in adapting the project for efficient deployment and ensuring compatibility with the Azure platform, as well as ML model deployment.
pythonjupyter-notebookoperationalizationimage-classificationmicrosoft
youngpark/computervision-recipes
Jan 2020 - Sep 2020
Best Practices, code samples, and documentation for Computer Vision.
Contributions:81 pushes, 28 branches in 8 months
pytorchpythonvisiondeep-learningimage-segmentation
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