When does a company actually decide to hire an ML engineer instead of just using APIs? [D]

I’m trying to understand this from a real-world perspective. Right now, it feels like you can get very far just using existing models (LLMs, embeddings, etc.) through APIs. You can build solid products without ever training a model yourself. So my question is: At what point does a company actually need to hire an ML engineer? Not in theory, but in practice. Some situations I’m thinking about: Is it when API costs get too high at scale? When they need better performance on their own data