Multi-objective ranking with tunable weights
Design the ranking layer for a feed that must optimize *multiple competing objectives at once*: predicted click, predicted long-dwell, predicted 'meaningful interaction' (comment/share), and a penalty for low-quality/clickbait. Each is a separate model producing a probability; the final order must combine them into one score. Product keeps wanting to retune the balance (push 'meaningful interactions' up before an election; push dwell up to grow watch time) without a code deploy. Design the scoring and the tuning mechanism.
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.
Clarify5:30 left
Estimate5:30 planned
Design16:30 planned
Deep dive13:30 planned
Failure9:00 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.