Shelley Winner
Surface Specialist at Microsoft
Rancho Cordova, California, United States
Summary
🤩
Rockstar🎓
Top SchoolShelley Winner is a Surface Specialist at Microsoft with seven years of hands-on experience bridging technical solutions and customer success across enterprise accounts. She combines deep product and pre-sales expertise—spanning Surface devices, Windows management, security, and cloud-enabled workflows—with proven skills in pipeline and deal orchestration to drive adoption and revenue. Shelley pairs this commercial experience with practical technical contributions to MLOps projects on high-profile Microsoft repos, integrating tracking and deployment examples for Azure Machine Learning and FastAI-based image classification notebooks. Her background includes frontline service and field technician roles, giving her a rare end-to-end perspective from hardware troubleshooting to strategic solution design. A compelling public speaker and advocate, she has shared her personal journey to break hiring stigmas and promote inclusive talent practices. Based in Rancho Cordova, CA, she blends technical curiosity, operational rigor, and a talent for storytelling to help customers envision and realize digital transformation.
7 years of coding experience
1 year of employment as a software developer
American River CollegeComputer Science, 4.0, Computer Science, 4.0 at City College of San Francisco
Github Skills (17)
notebook10
python10
azure-machine-learning10
fastai10
mlops10
jupyter-notebook10
machine-learning9
azure-container-apps9
azure-container-instances9
computer-vision8
data-science8
microsoft-azure7
dockers7
docker7
azure7
Programming languages (5)
Github contributions (5)
Azure/MachineLearningNotebooks
Apr 2019 - Feb 2020
Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft
Role in this project:
MLOps Engineer
MLOps EngineerContributions:382 commits, 19 PRs, 380 pushes in 9 months
Contributions summary:Shelley's primary contributions involve integrating a pixel tracking system into various Azure Machine Learning Notebooks. This includes adding tracking pixels to multiple notebooks across different how-to-use-azureml examples, specifically within the machine-learning-pipelines section. Furthermore, the user updated the "config" text in several notebooks, ensuring correct configuration instructions for the notebooks. The user also updated notebook prerequisites.
pythontensorflowmicrosoftsdk-pythondata-science
microsoft/MLOps
Mar 2020 - Mar 2020
MLOps examples
Role in this project:MLOps Engineer
MLOps EngineerContributions:15 commits, 1 PR, 1 comment in 1 day
Contributions summary:Shelley primarily contributes to examples related to training and deploying Fastai image classification models within the Azure Machine Learning environment. Their work involves modifying and creating Jupyter notebooks that demonstrate local and remote training, model registration, and deployment to Azure Container Instances. They integrate metrics logging and environment setup for ML model development and deployment.
cmlmlopsmachine-learningazure-machine-learningkubernetes
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