On-device model deployment and telemetry
Design the system that ships and runs an on-device computer-vision model on 50M smartphones (e.g. a real-time camera segmentation feature). Inference runs locally for privacy and latency, but the model must be updatable over the air, must work on a wide range of device capabilities, and you need to know in aggregate whether a new model version is actually better — all without uploading users' images. Design the on-device inference + update + telemetry system.
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.
Clarify4:30 left
Estimate4:30 planned
Design13:30 planned
Deep dive10:30 planned
Failure7:00 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.