@sparring/tech-roles-library
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Comprehensive tech roles and competencies library for 78 technical roles with 9 career levels each. Includes detailed competencies and career progression paths with complete bilingual support (EN/ES).
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{
"role": "MLOps Architect",
"category": "Data",
"levels": {
"MLOA-L1": {
"level": "L1 - MLOps Trainee",
"levelNumber": 1,
"yearsRange": {
"min": 0,
"max": 1
},
"coreCompetencies": [
"Basic knowledge of MLOps principles",
"Elementary understanding of ML pipelines",
"Ability for basic model versioning",
"Basic knowledge of ML containerization",
"Simple deployment capability",
"Understanding of basic monitoring",
"Documentation of ML workflows",
"Elementary knowledge of reproducibility"
],
"complementaryCompetencies": [
"Familiarity with basic MLflow",
"Knowledge of Git for ML",
"Understanding of Docker for ML"
],
"indicators": [
"Requires constant supervision",
"Implements simple ML pipelines",
"Is learning MLOps architecture"
]
},
"MLOA-L2": {
"level": "L2 - Junior MLOps Engineer",
"levelNumber": 2,
"yearsRange": {
"min": 1,
"max": 2
},
"coreCompetencies": [
"Capability to design end-to-end pipelines",
"Implementation of CI/CD for ML",
"Practical knowledge of orchestration",
"Ability for feature stores",
"Understanding of model registry",
"A/B testing capability for ML",
"Knowledge of drift detection",
"Ability for automated retraining"
],
"complementaryCompetencies": [
"Development of model serving APIs",
"Knowledge of Kubernetes for ML",
"Understanding of data versioning"
],
"indicators": [
"Designs MLOps pipelines with supervision",
"Implements ML automation",
"Maintains ML infrastructure"
]
},
"MLOA-L3": {
"level": "L3 - MLOps Engineer",
"levelNumber": 3,
"yearsRange": {
"min": 2,
"max": 3
},
"coreCompetencies": [
"Design of enterprise MLOps architectures",
"Implementation of ML platforms",
"Mastery of distributed training infrastructure",
"Multi-cloud MLOps capability",
"Ability for governance frameworks",
"Deep knowledge of observability",
"Implementation of edge ML deployment",
"Design of experimentation platforms"
],
"complementaryCompetencies": [
"Knowledge of federated learning ops",
"Ability for ML cost optimization",
"Understanding of MLOps compliance"
],
"indicators": [
"Leads MLOps initiatives",
"Designs scalable ML platforms",
"Mentors MLOps engineers"
]
},
"MLOA-L4": {
"level": "L4 - Senior MLOps Engineer",
"levelNumber": 4,
"yearsRange": {
"min": 3,
"max": 5
},
"coreCompetencies": [
"Architecture of MLOps ecosystems",
"Design of global ML infrastructure",
"Implementation of AutoML platforms",
"Mastery of ML reliability engineering",
"ML platform engineering capability",
"Deep knowledge of ML economics",
"Ability for MLOps standards",
"Leadership in MLOps innovation"
],
"complementaryCompetencies": [
"Experience in real-time ML systems",
"Knowledge of quantum ML ops",
"Implementation of green ML"
],
"indicators": [
"Defines enterprise MLOps strategy",
"Leads ML platform teams",
"Is a reference in ML infrastructure"
]
},
"MLOA-L5": {
"level": "L5 - Lead MLOps Engineer",
"levelNumber": 5,
"yearsRange": {
"min": 5,
"max": 7
},
"coreCompetencies": [
"Technical leadership in MLOps",
"Design of MLOps transformation programs",
"Management of ML platform teams",
"Definition of ML infrastructure strategy",
"MLOps center of excellence capability",
"Implementation of self-service ML",
"Mastery of ML democratization",
"Evangelization of MLOps culture"
],
"complementaryCompetencies": [
"Experience in MLOps consulting",
"Knowledge of industry MLOps standards",
"Management of MLOps vendors"
],
"indicators": [
"Manages MLOps organization",
"Defines enterprise ML platform vision",
"Represents MLOps to executives"
]
},
"MLOA-L6": {
"level": "L6 - Principal MLOps Architect",
"levelNumber": 6,
"yearsRange": {
"min": 7,
"max": 10
},
"coreCompetencies": [
"Direction of organizational MLOps",
"Global ML infrastructure strategy",
"Management of ML platform investments",
"Definition of AI operations strategy",
"Leadership in MLOps transformation",
"Implementation of autonomous ML ops",
"Innovation in MLOps paradigms",
"Management of global ML infrastructure"
],
"complementaryCompetencies": [
"Experience in MLOps for critical products",
"Knowledge of regulatory MLOps",
"Leadership in MLOps communities"
],
"indicators": [
"Directs MLOps department (20+ people)",
"Participates in AI strategy",
"Defines investments in ML infrastructure"
]
},
"MLOA-L7": {
"level": "L7 - Director MLOps",
"levelNumber": 7,
"yearsRange": {
"min": 10,
"max": 12
},
"coreCompetencies": [
"Executive leadership in ML operations",
"Design of global MLOps strategies",
"Enterprise transformation via MLOps",
"Management of MLOps at Fortune 500 scale",
"Creation of new operational paradigms",
"Definition of the future of ML infrastructure",
"MLOps evangelization at board level",
"Influence in ML industry"
],
"complementaryCompetencies": [
"Management of MLOps at hyperscale",
"Experience in MLOps unicorns",
"Leadership in MLOps standards bodies"
],
"indicators": [
"Reports to CTO/CDO",
"Manages MLOps organization (50+ people)",
"Defines corporate ML operations strategy"
]
},
"MLOA-L8": {
"level": "L8 - VP MLOps",
"levelNumber": 8,
"yearsRange": {
"min": 12,
"max": 15
},
"coreCompetencies": [
"Strategic vision of autonomous ML operations",
"Leadership in MLOps revolution",
"Creation of self-managing ML paradigms",
"Planetary MLOps management",
"Disruptive innovation in ML automation",
"Definition of sentient MLOps",
"Evangelization of ML singularity ops",
"Influence in the future of AI operations"
],
"complementaryCompetencies": [
"Experience as VP MLOps in tech giants",
"Advisory in MLOps platforms",
"Thought leadership in ML infrastructure"
],
"indicators": [
"Is part of AI leadership",
"Defines the future of MLOps",
"Is a world leader in ML operations"
]
},
"MLOA-L9": {
"level": "L9 - VP MLOps/Head ML Platform",
"levelNumber": 9,
"yearsRange": {
"min": 15,
"max": null
},
"coreCompetencies": [
"Visionary leadership in the future of ML operations",
"Transformation of AI via perfect ops",
"Creation of eternal ML systems paradigms",
"Definition of conscious ML infrastructure",
"Innovation in biological MLOps",
"Evangelization of ML omnipresence",
"Architect of ML reality",
"Influence in the evolution of operational intelligence"
],
"complementaryCompetencies": [
"Creator of MLOps revolutions",
"Recognition as father of modern MLOps",
"Influence in the future of AI operations"
],
"indicators": [
"Is legendary Chief MLOps Officer",
"Defines the future of ML operations",
"Is world authority in MLOps"
]
}
}
}