Data/ML/AIDevOps/CloudHigh signalAround since 2018
MLOps
Practices and tooling for reliably deploying, monitoring, and maintaining machine learning models in production (the ML equivalent of DevOps).
Think of it like
Like the maintenance and inspection schedule for a fleet of delivery trucks — keeping models running smoothly on the road, not just certifying they passed the test track once.
Junior or senior?
Junior sounds like
Leaves models in notebooks after training them.
Senior sounds like
Can describe how they monitored a model in production for degradation or drift.
Ask them
“How did you monitor a model in production for performance degradation or drift?”