MLOps
Operationalizing machine learning pipelines and models
Linked Roles
2
Readiness Models
1
Recorded People
1
Competency Overview
Operationalizing machine learning models through repeatable training, deployment, monitoring and lifecycle practices.
Key capabilities
- Model delivery pipelines
- Experiment and artifact traceability
- Production monitoring and drift awareness
Where it's used
See all relationships →AI Architect
Role · Required · L4/5
AI Lead
Role · Required · L4/5
AI Implementation
Readiness · L3/5
Links reflect current Role and Readiness Model requirements, not verified staff qualifications.
Proficiency Reference
General TalentForge 1–5 scale. Skill-specific observable criteria have not been defined.
AwarenessRecognizes the core concepts and terminology.
BasicPerforms routine activities with guidance.
ProficientWorks independently in common situations.
AdvancedHandles complex cases and supports others.
ExpertProvides expert guidance and sets good practices.
Levels 1–5 are ordinal, not percentages. Criteria describe skills; they are not personal assessments.
Catalog Information — identifiers, classifications and scope
- Skill ID
skill-mlops- Primary family
- Data & AI
- Category
- Machine Learning Operations
- Type
- Technical
- Aliases
- None recorded
- Tags
- None recorded
- Status
- Active
- Definition version
- 1
Competency scope
ML system delivery and operations; distinct from the research and modeling skill.