On-device keyboard prediction
Design an on-device + cloud ML inference system for a mobile keyboard's next-word/auto-correct prediction used by 500M devices, where predictions must run locally in under 20ms with no network dependency, models must update over the air, and personalization must respect on-device privacy (typed text shouldn't leave the device). Cover the on-device model, the update mechanism, how personalization works without sending raw data, and the cloud's role.
What a strong answer looks like
Clarify scale and constraints first. Propose a clean component breakdown, then go deep on the hard parts (data model, bottlenecks, consistency, failure modes) and name the trade-offs you are making.
Clarify5:00 left
Estimate5:00 planned
Design15:00 planned
Deep dive12:00 planned
Failure8:00 planned
Which questions mattered is sealed until you submit. Telling you now would just be handing over the edge cases.
Run or narrate your approach, then ask the coach.