How do you train a reward model from preference data, and what are the key design choices?
A reward model converts pairwise preferences into a scalar signal RLHF can optimize. The signal is the Bradley-Terry loss, the base-model and head choices, and how you validate it before trusting it.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
A reward model converts pairwise preferences into a scalar signal RLHF can optimize. The signal is the Bradley-Terry loss, the base-model and head choices, and how you validate it before trusting it.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
