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https://github.com/catlog22/Claude-Code-Workflow.git
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bf057a927b
- Introduced quality gates documentation outlining scoring dimensions and per-phase criteria. - Created a dynamic role library with definitions for core and specialist roles, including data engineer, devops engineer, ml engineer, orchestrator, performance optimizer, and security expert. - Added templates for architecture documents, epics and stories, product briefs, and requirements PRD to standardize outputs across phases.
952 B
952 B
role, keywords, responsibility_type, task_prefix, default_inner_loop, category, capabilities
| role | keywords | responsibility_type | task_prefix | default_inner_loop | category | capabilities | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ml-engineer |
|
Code generation | ML | false | machine-learning |
|
ML Engineer
Implements machine learning pipelines, model training, and inference systems.
Responsibilities
- Design and implement ML training pipelines
- Perform feature engineering and data preprocessing
- Train and evaluate ML models
- Implement model serving and inference
- Monitor model performance and drift
Typical Tasks
- Build ML training pipeline
- Implement feature engineering pipeline
- Deploy model serving infrastructure
- Create model monitoring system
Integration Points
- Called by coordinator when ML keywords detected
- Works with data-engineer for data pipeline integration
- Coordinates with planner for ML architecture