{
  "id": "role:ml-ops-engineer",
  "_kind": "Role",
  "_file": "domain/roles/roles-data.yaml",
  "_cluster": "domain",
  "attributes": {
    "displayName": "MLOps Engineer",
    "isAgentic": false,
    "automatability": 0.7,
    "description": "Builds and maintains the infrastructure and tooling that enables data scientists\nand ML engineers to train, evaluate, deploy, and monitor machine learning models\nin production efficiently. Owns the ML platform stack including experiment\ntracking, feature stores, model registries, and serving infrastructure. Bridges\nthe operational gap between research and production, ensuring models degrade\ngracefully and can be retrained and redeployed with minimal friction.\n",
    "seniority": "senior"
  },
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      "kind": "holds_responsibility"
    },
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      "to": "responsibility:on-call",
      "kind": "holds_responsibility"
    },
    {
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      "to": "responsibility:capacity-planning",
      "kind": "holds_responsibility"
    },
    {
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      "to": "responsibility:performance-optimization",
      "kind": "holds_responsibility"
    },
    {
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      "kind": "holds_responsibility"
    },
    {
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      "kind": "requires_skill",
      "attributes": {
        "level": "expert"
      }
    },
    {
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      "to": "domain:cloud-infra",
      "kind": "requires_skill",
      "attributes": {
        "level": "expert"
      }
    },
    {
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      "to": "specialization:devops-sre-platform",
      "kind": "requires_skill",
      "attributes": {
        "level": "intermediate"
      }
    },
    {
      "from": "role:ml-ops-engineer",
      "to": "specialization:k8s-ops",
      "kind": "requires_skill",
      "attributes": {
        "level": "intermediate"
      }
    }
  ],
  "incomingEdges": [
    {
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      "to": "role:ml-ops-engineer",
      "kind": "used_by_role"
    },
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    },
    {
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    },
    {
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      "kind": "involves_role"
    },
    {
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      "attributes": {
        "weight": 1
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    },
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}