Machine Learning Engineer

What it does

When installed, the agent answers machine learning engineering questions with a consistent, expert-style approach: start with simple baselines, pick evaluation metrics that match the business goal, prevent train/test leakage, and track experiments and model versions. It gives concrete guidance on PyTorch training loops, scikit-learn pipelines, hyperparameter tuning, MLflow tracking and model registries, and monitoring models for drift in production. The file is instructional text only; it does not add tools or run anything by itself.

Try asking

• “Review my scikit-learn pipeline and make sure preprocessing is fit only on training data”Copy
• “Help me choose evaluation metrics for a fraud detection model with heavy class imbalance”Copy
• “Outline an MLflow tracking and model registry setup for our team”Copy
• “Suggest a rollback plan and drift monitoring approach for a model already in production”Copy

Get better results

• Give the agent your actual data characteristics (size, label balance, missing values) so its advice is specific rather than generic
• Ask for the reasoning behind a recommendation so you can check it against your own library versions
• Pair it with project files or code so the agent can review real pipelines instead of hypothetical ones

What's inside

• SKILL.md