IT AI Skill

Ai Ml Operations

Manage AI/ML model lifecycle including model deployment orchestration, feature store management, model monitoring and drift detection, automated retraining pipelines, model governance and compliance, A/B testing frameworks, and ML cost optimization. Use when deploying ML models to production, monitoring model performance degradation, managing feature stores, automating retraining cycles, establishing ML governance frameworks, conducting model audits, or optimizing ML infrastructure costs. Triggers on phrases like "ML operations", "MLOps", "model deployment", "model monitoring", "feature store", "model drift", "automated retraining", "ML governance", "model registry", "inference optimization", "model versioning", "ML pipeline", "model audit", "canary deployment", "model rollback".