Garnet Vaz
Principal Data Scientist
United States
Summary
👤
Senior🎓
Top SchoolGarnet Vaz is a Principal Data Scientist at Microsoft CoreAI with 12 years of experience building the telemetry and intelligence layer that powers global AI infrastructure. He designs large-scale data pipelines and monitoring systems that turn raw GPU and inference telemetry into actionable insights for workload placement, capacity planning, and cost-efficient fleet operations. Garnet led cross-organizational experimentation and observability efforts for Copilot-era infrastructure, advancing rigorous experimentation frameworks and instrumentation best practices across product teams. His PhD in Applied Mathematics underpins a strong grounding in scalable algorithms and performance modeling, which he applies to detect anomalies and validate system regressions at scale. He is especially focused on data quality and trust frameworks that make operational telemetry dependable for decision-making across CoreAI. Colleagues rely on him to bridge systems, applied AI, and engineering strategy to multiply the impact of every model deployed on Microsoft’s GPU fleet.
12 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Applied Mathematics, Doctor of Philosophy (Ph.D.), Applied Mathematics at University of California, MercedM.S, Applied Mathematics & Statistics, M.S, Applied Mathematics & Statistics at Stony Brook University
Github Skills (8)
editor9
vscode9
electron9
typescript9
visual-studio-code8
microsoft8
vscode-extension8
visual-studio8
Programming languages (1)
Github contributions (4)
GarnetVaz/Quantile-trees
Feb 2014 - Mar 2014
Contributions:76 commits in 27 days
GarnetVaz/flask-app
Oct 2016 - Oct 2016
Contributions:11 pushes, 1 branch in 6 days
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