The Importance of Metrics for Success in MLOps

Is the person being measured on this ability to build a reliable and maybe repeatable and scalable pipeline? Is that the actual data science or is that the MLOps engineer like who is doing that? And I know like titles are complicated thing. But yeah, it's different everywhere. It's different everywhere, but somebody needs to do it. Ideally, it's like an expert at ML and an expert in data, but those so hard to find. So maybe somebody was more of an engineer. Do you think that? No, that's that's fair. It's a hard question for that.

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