Your question is ML Models in Production Systems. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How would you approach integrating machine learning models into production systems?
Discuss the end-to-end process from problem definition and data preparation through training, deployment, online or batch inference, monitoring, and retraining. Explain how you would choose an architecture under realistic production constraints, validate model and system performance, handle model and feature failures, and prevent training-serving skew. Be prepared to state assumptions, identify requirements that must be clarified, and explain tradeoffs between speed, reliability, cost, and model quality.