machine learning engineering

“Like what you should write down is like, here are the conditions. This is the inputs and the outputs we tried the experiment on. And then one thing that's really valuable is basically writing down under what conditions would I revisit these experiments?”

“I think a lot more data science is going to come in versus machine learning engineering, because a lot of it now is just quantifying, like, what does the business actually want as an outcome, right?”

“So, agency lets you sort of capture the volume of experiments, and, like, experience lets you figure out, like, oh, that other half, it's not worth doing.”