TAYLOR BROOKS
Boston, MA · taylor.brooks@email.com · (555) 010-1202 · linkedin.com/in/taylorbrooksml

SUMMARY
ML engineer with 2+ years taking models from training to production: feature pipelines, GPU jobs, MLflow tracking, and Kubernetes serving with drift alerts. Focused on reliability metrics PMs can operate on.

SKILLS
Python · PyTorch / TensorFlow · Model deployment (serving) · MLOps (MLflow) · Feature pipelines · Kubernetes / Docker · Drift monitoring · GPU training

EXPERIENCE
Machine Learning Engineer · Cobalt Health · 2023-Present
• Deployed a gradient-boosted readmission model; reduced false alerts 23% after calibration + threshold tuning.
• Built MLflow-backed training pipeline on GPU nodes; cut experiment turnaround from 2 days to 4 hours.
• Owned Docker/K8s scoring service (p95 < 120ms); added drift monitors that paged on PSI breaches.

ML Engineer Intern → Jr · Harbor Labs · 2022-2023
• Productionized a PyTorch text classifier; replaced brittle regex rules covering 31% of tickets.

EDUCATION
MS Machine Learning · New England Tech · 2022