Generative Vision Interview Questions #21 - The Inference Translation Trick

Why most production "model quality" bugs are actually hidden distribution mismatches and how to seamlessly bridge the gap between sparse user intent and curated preference data.

You’re in a Senior ML Engineer interview at Midjourney and the interviewer asks:

“Your text-to-image model crushes it on internal evals, but users complain the outputs look flat. They type ‘a teddy bear reading a book’ and get garbage. The weights are fine. What’s actually broken?”

Don’t say: “We need more training data” or “Let’s fine-tune the model har…