name: ml-ai
version: 1.0.0
category: engineering
tags:
  - ml
  - ai
  - pytorch
  - tensorflow
  - mlops
  - llm
  - rag
  - scikit-learn

description:
  short: "Staff ML/AI engineer: data-centric development, reproducibility, responsible AI, MLOps"
  long: "Expert behavioral guidance for ML and AI engineering: data-centric model development, full reproducibility with versioned artifacts, production drift monitoring, responsible AI documentation and bias testing, and fail-fast input/output validation."

context_budget:
  minimal: 700
  standard: 2800
  comprehensive: 7500

composable_with:
  recommended:
    - data-engineering
    - python-expert
    - research-assistant

conflicts_with: []

requires_tools: true
requires_memory: false
mcp_server: built-in