Welcome to your interview.
The question is on your right: Evaluating Model Robustness in Production. Take a moment with it first.
Talk your thinking through with me if you like - when you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes). Discussion and graded submissions share your five interviewer interactions, so spend them well.
You've built a machine learning model that looks good in offline testing, and your team wants confidence that it will hold up when data and usage patterns change. You need a practical evaluation approach that goes beyond a single validation score.
How do you ensure that your machine learning models are robust?