@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 Engineer",
"category": "Software Engineering",
"levels": {
"MLO-L1": {
"level": "L1 - MLOps Trainee",
"levelNumber": 1,
"yearsRange": {
"min": 0,
"max": 1
},
"coreCompetencies": [
"Basic understanding of ML lifecycle",
"Elementary knowledge of model versioning",
"Ability for simple model deployment",
"Basic understanding of data pipelines",
"Basic model monitoring capability",
"Elementary knowledge of containerization for ML",
"Basic understanding of reproducibility",
"Ability to document experiments"
],
"complementaryCompetencies": [
"Basic knowledge of cloud ML services",
"Familiarity with notebooks and Git",
"Elementary understanding of CI/CD"
],
"indicators": [
"Requires constant supervision",
"Can execute existing pipelines",
"Needs 6-12 months of MLOps mentoring"
]
},
"MLO-L2": {
"level": "L2 - Junior I",
"levelNumber": 2,
"yearsRange": {
"min": 1,
"max": 2
},
"coreCompetencies": [
"Capability to implement basic ML pipelines",
"Ability to automate training and deployment",
"Practical knowledge of experiment tracking",
"Understanding of model registry and governance",
"Capability to implement basic monitoring",
"Ability for data versioning",
"Knowledge of A/B testing for models",
"Understanding of basic model serving"
],
"complementaryCompetencies": [
"Knowledge of Kubernetes for ML",
"Ability for basic feature stores",
"Understanding of data quality monitoring"
],
"indicators": [
"Implements pipelines with supervision",
"Maintains models in production",
"Resolves common deployment issues"
]
},
"MLO-L3": {
"level": "L3 - Junior II",
"levelNumber": 3,
"yearsRange": {
"min": 2,
"max": 3
},
"coreCompetencies": [
"Mastery of ML pipeline orchestration",
"Capability to implement continuous training",
"Ability for drift detection and monitoring",
"Deep knowledge of model optimization",
"Capability to implement feature engineering pipelines",
"Solid understanding of distributed training",
"Ability for rollback and versioning strategies",
"Knowledge of edge deployment"
],
"complementaryCompetencies": [
"Knowledge of AutoML platforms",
"Ability for federated learning ops",
"Understanding of explainability pipelines"
],
"indicators": [
"Designs complete MLOps pipelines",
"Optimizes inference performance",
"Implements MLOps best practices"
]
},
"MLO-L4": {
"level": "L4 - Mid-Level I",
"levelNumber": 4,
"yearsRange": {
"min": 3,
"max": 5
},
"coreCompetencies": [
"Capability to architect MLOps platforms",
"Mastery of model governance and compliance",
"Ability to implement feature platforms",
"Deep knowledge of scalable serving",
"Capability to implement advanced monitoring",
"Mastery of cost optimization for ML",
"Ability for multi-model serving",
"Knowledge of ML security and privacy"
],
"complementaryCompetencies": [
"Knowledge of real-time ML",
"Ability for multi-cloud MLOps",
"Understanding of green ML"
],
"indicators": [
"Defines MLOps strategy for products",
"Leads adoption of MLOps practices",
"Mentors MLOps engineers"
]
},
"MLO-L5": {
"level": "L5 - Mid-Level II",
"levelNumber": 5,
"yearsRange": {
"min": 5,
"max": 7
},
"coreCompetencies": [
"Expertise in enterprise MLOps platforms",
"Capability to design ML infrastructure at scale",
"Mastery of advanced experimentation platforms",
"Ability to implement ML observability",
"Deep knowledge of regulatory compliance for ML",
"Capability to implement MLOps automation",
"Expertise in distributed ML systems",
"Mastery of ML pipeline optimization"
],
"complementaryCompetencies": [
"Knowledge of quantum ML ops",
"Ability for neuromorphic deployment",
"Understanding of MLOps economics"
],
"indicators": [
"Architects MLOps for portfolios",
"Leads MLOps transformation",
"Defines corporate MLOps standards"
]
},
"MLO-L6": {
"level": "L6 - Senior I",
"levelNumber": 6,
"yearsRange": {
"min": 7,
"max": 10
},
"coreCompetencies": [
"Capability to define enterprise MLOps strategy",
"Expertise in ML platform engineering",
"Mastery of ML reliability engineering",
"Ability for MLOps governance frameworks",
"Deep knowledge of ML economics",
"Capability to lead MLOps innovation",
"Expertise in ML vendor management",
"Mastery of MLOps risk management"
],
"complementaryCompetencies": [
"Knowledge of AI ethics implementation",
"Ability for MLOps consulting",
"Understanding of ML ventures"
],
"indicators": [
"Defines multi-year MLOps roadmap",
"Leads MLOps organizations",
"Influences MLOps industry"
]
},
"MLO-L7": {
"level": "L7 - Senior II",
"levelNumber": 7,
"yearsRange": {
"min": 10,
"max": 12
},
"coreCompetencies": [
"Leadership in global MLOps innovation",
"Capability to create MLOps competitive advantages",
"Expertise in MLOps business models",
"Mastery of ML platform economics",
"Capability to define MLOps philosophy",
"Deep knowledge of ML democratization",
"Expertise in MLOps partnerships",
"Capability to lead MLOps research"
],
"complementaryCompetencies": [
"Capability to patent MLOps innovations",
"Ability for MLOps evangelism",
"Knowledge of MLOps investments"
],
"indicators": [
"Defines corporate MLOps philosophy",
"Keynote speaker at MLOps conferences",
"Thought leader in MLOps"
]
},
"MLO-L8": {
"level": "L8 - Principal/Chief",
"levelNumber": 8,
"yearsRange": {
"min": 12,
"max": 15
},
"coreCompetencies": [
"Strategic vision of the future of MLOps",
"Capability to transform companies through MLOps",
"Expertise in executive MLOps strategy",
"Mastery of ML infrastructure economics",
"Capability to define MLOps excellence",
"Deep knowledge of ML platform governance",
"Expertise in MLOps ecosystem building",
"Capability to lead MLOps standards"
],
"complementaryCompetencies": [
"Capability to influence MLOps regulations",
"Ability for MLOps ventures",
"Knowledge of MLOps M&A"
],
"indicators": [
"Defines MLOps strategy for Fortune 500",
"Influences global MLOps platforms",
"Executive MLOps advisor"
]
},
"MLO-L9": {
"level": "L9 - VP MLOps/Head ML Platform",
"levelNumber": 9,
"yearsRange": {
"min": 15,
"max": null
},
"coreCompetencies": [
"Executive leadership in ML infrastructure",
"Capability of MLOps as differentiator",
"Expertise in ML platform transformation",
"Mastery of ML infrastructure budgets",
"Capability to build MLOps organizations",
"Deep knowledge of ML platform strategy",
"Expertise in executive ML partnerships",
"Capability to define ML platform culture",
"Mastery of ML value delivery"
],
"complementaryCompetencies": [
"Capability of ML policy influence",
"Ability for ML ecosystem creation",
"Knowledge of ML platform exits"
],
"indicators": [
"Defines and executes enterprise MLOps vision",
"Responsible for all ML infrastructure",
"Recognized leader in global MLOps"
]
}
}
}