Generative Vision Interview Questions, issue 21, Jun 29, 2026
The Inference Translation Trick
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”
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.
The full answer, with the mechanism and the arithmetic, is for paid subscribers on Substack.