By wshobson
Orchestrate end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment, integrating with Airflow, Dagster, or Kubeflow for workflow automation.
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Dependency auditing, version management, and security vulnerability scanning
SAST analysis, dependency vulnerability scanning, OWASP Top 10 compliance, container security scanning, and automated security hardening
Database architecture, schema design, and SQL optimization for production systems
ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows
ETL pipeline construction, data warehouse design, batch processing workflows, and data-driven feature development
npx claudepluginhub p/wshobson-wshobson-ml-pipeline-workflow-plugins-machine-learning-ops-skills-ml-pipeline-workflowML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows
Automate ML workflows with Airflow, Kubeflow, MLflow. Use for reproducible pipelines, retraining schedules, MLOps, or encountering task failures, dependency errors, experiment tracking issues.
ML engineering agents providing expertise in MLOps, model deployment, and inference optimization
Deploy ML models to production
Data engineering, ML, and AI specialists - data pipelines, machine learning, LLM architecture
AI/ML development: LLM architecture, prompt engineering, ML ops, and NLP with production deployment focus