A model shipped bad predictions to production for six hours. Walk me through the incident response.
ML incidents are trickier than service outages: nothing crashed, the model was just wrong. The strong answer covers detection, mitigation, and a blameless postmortem that fixes the system, not the person.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
ML incidents are trickier than service outages: nothing crashed, the model was just wrong. The strong answer covers detection, mitigation, and a blameless postmortem that fixes the system, not the person.
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.
