Stacy Andrews
Software Engineering Manager, HPC And AI at Hewlett Packard Enterprise
Washington DC-Baltimore Area United States
Summary
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Rockstar🎓
Top SchoolStacy Andrews is a software engineering manager specializing in HPC and AI, currently leading distributed engineering teams at Hewlett Packard Enterprise after scaling agritech systems at Indigo. With a PhD in Management Sciences and a background in operations research, she blends rigorous modeling and optimization experience with hands-on backend engineering for large-scale data processing and verification pipelines. She has built services that enable millions of acres of agronomic data to be validated, imputed, and transformed into verified carbon credits, while promoting team growth through mentorship and promotions. Her early research produced peer-reviewed work on dynamic last-mile routing and custom HPC job-restart tooling, reflecting a practical comfort with high-performance computation and production reliability. Colocated in the Washington DC–Baltimore area, Stacy is effective at cross-functional collaboration across data science, product, and policy to deliver scalable, auditable systems.
2 years of coding experience
11 years of employment as a software developer
Bachelor of Arts (B.A.) Mathematics, Bachelor of Arts (B.A.) Mathematics at Coe CollegeDoctor of Philosophy (PhD) Management Sciences, Doctor of Philosophy (PhD) Management Sciences at University of Iowa
English
Github Skills (12)
keras10
hyperparameter-tuning10
data-science9
tensorflow9
machine-learning9
distributed-training9
mlops9
deep-learning9
hyperparameter-optimization9
pytorch9
kubernetes9
model-management8
Programming languages (1)
Github contributions (1)
determined-ai/determined
Feb 2024 - Jul 2024
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
Contributions:3 reviews, 30 PRs, 269 branches in 4 months
pytorchdata-sciencedeep-learningdistributed-trainingmachine-learning
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