Heather Spetalnick
Principal Technical Program Manager at Amazon
New York City Metropolitan Area United States
Summary
🤩
Rockstar🎓
Top SchoolHeather Spetalnick is a Principal Technical Program Manager with 11 years of experience orchestrating complex, cross-functional AI and cloud initiatives from Microsoft to Amazon. She combines product-minded program leadership with hands-on ML and MLOps experience—contributing practical examples and docs to well-known Microsoft repos for NLP, computer vision, and recommender systems. At Amazon she has driven privacy-by-design and large-scale platform delivery for Alexa and led Co-Viewing and search improvements for Prime Video, consistently translating research and architecture into customer-facing features. She has a strong engineering foundation from Duke in statistical science and computer science, and a track record of operationalizing models on Azure (ACI/AKS) and integrating monitoring like PixelServer. Known for improving clarity as much as code, she often focuses on documentation, reproducibility, and accessible UX for data scientists. Based in the NYC area, she balances strategic roadmapping with detail-oriented execution across ML lifecycle and privacy initiatives.
11 years of coding experience
7 years of employment as a software developer
Bachelor of Science (BS) Statistical Science (With Distinction) Computer Science, Bachelor of Science (BS) Statistical Science (With Distinction) Computer Science at Duke University
Spanish
Stackoverflow
31reputation
757reached
3answers
0questions
Github Skills (31)
notebook10
kubernetes10
pytorch10
docker10
python10
machine-learning10
pyspark10
microsoft-azure10
azure-machine-learning10
dockers10
mlops10
question-answering10
bert10
natural-language-processing10
kubernetes-pods10
Programming languages (10)
Github contributions (5)
microsoft/nlp-recipes
Jun 2019 - Sep 2019
Natural Language Processing Best Practices & Examples
Role in this project:
ML Engineer
ML EngineerContributions:28 commits, 1 PR, 5 pushes in 3 months
Contributions summary:Heather primarily updated and refined existing notebooks within the `nlp-recipes` repository, focusing on the fine-tuning of BERT models for various NLP tasks such as question answering and natural language inference. Their commits involved modifications to text, table of contents, and links within the notebooks, as well as adjustments to the code and overall structure. These changes suggest a focus on improving the clarity, usability, and accuracy of the examples demonstrating BERT implementation.
natural-language-understandingnluword-embeddingslanguage-processingdialogue-systems
microsoft/computervision-recipes
Jun 2019 - Aug 2019
Best Practices, code samples, and documentation for Computer Vision.
Role in this project:MLOps Engineer
MLOps EngineerContributions:15 commits, 2 PRs, 3 pushes in 2 months
Contributions summary:Heather's contributions primarily involve deploying and testing machine learning models within an Azure environment. Their work includes integrating PixelServer to monitor model performance. They modified existing notebooks to reflect Azure Container Instances (ACI) and Azure Kubernetes Service (AKS) deployments, highlighting their focus on operationalizing ML models. The user also made changes to include Azure workspace setup and testing procedures in the notebooks.
pythonjupyter-notebookoperationalizationimage-classificationmicrosoft
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