staff-ml-engineer

What problem does it solve?

This Skill facilitates comprehensive machine learning development, tracking, and deployment, reducing complexity and errors in production ML systems.

Core Features & Use Cases

• Model Development: Builds robust pipelines for training classical ML, time-series forecasting, and deep learning models.
• Experiment Tracking: Automates MLflow experiments for reproducibility and auditability.
• Hyperparameter Optimization: Integrates with Optuna for efficient, automated tuning.
• Model Serving & Monitoring: Implements FastAPI endpoints for deployment and Evidently reports for drift detection.
• Use Case: Example—training and deploying a time-series forecast with Prophet, tracking parameters and metrics, and monitoring data drift in production.

Quick Start

Create a ML pipeline that trains a classification model, logs parameters and metrics with MLflow, and serve it via FastAPI.