Roles in MLOps

MLOps Concepts

Folkert Stijnman

ML Engineer

Machine learning lifecycle

• Business roles
• Technical roles

Business roles

• Business stakeholder
• Subject matter expert

Business roles: business stakeholder

• Budget decisions
• Vision of company
• Involved throughout the lifecycle

Business roles: subject matter expert

• Domain knowledge
• Involved throughout the lifecycle
• Interpret and validate data

Technical roles

• Data scientist
• Data engineer
• ML engineer

Technical roles: data scientist

• Data analysis
• Model training and evaluation

Technical roles: data engineer

• Collecting, storing, and processing data
• Check and maintain data quality

Technical roles: ML engineer

• Versatile role
• Specifically designed for complete machine learning lifecycle

Additional roles involved in ML

• Data analyst, developer, software engineer, backend engineer
• Responsbility of roles can vary depending on application of machine learning
• Startup is different from a large enterprise

Let's practice!

MLOps Concepts