Daily CTR model training pipeline
Design an end-to-end training pipeline for a click-through-rate model that retrains daily on ~5B labeled impressions, must produce a reproducible, validated model artifact, and feed a daily-refreshed online predictor. Latency to production (data ready → model live) should be under 4 hours, and a bad model must never reach 100% of traffic. Cover data ingestion/labeling, the orchestration, validation gates, and how offline training stays consistent with online serving.
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.
Clarify6:00 left
Estimate6:00 planned
Design18:30 planned
Deep dive14:30 planned
Failure10:00 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.