How would you go about scoping improvements to the quality of a machine learning model?

"A sourcer had been nudging me on LinkedIn for a while, so I never did a normal recruiter screen. Once I sent my resume, two hiring managers in the same Siri AI/ML org wanted to talk, so Apple ran one combined process for both EPM roles instead of making me do two separate loops. I did two hiring manager screens, then a joint onsite with a data science manager, an ML engineering manager, another behavioral round with one of the hiring managers, and a final conversation with a very senior engineering leader. The whole thing felt extremely team-dependent and very niche, especially the ML metrics parts, which is what made it different from more generic big-tech TPM loops. I finished in early December and got rejected."