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How do you test an ML system (beyond accuracy), including data, model, and behavioral tests?

A high accuracy number hides slice failures, brittleness, and silent data bugs. What counts is naming the test layers that catch what the headline metric can't. Here is the framework that gets scored highest.

Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.

A high accuracy number hides slice failures, brittleness, and silent data bugs. What counts is naming the test layers that catch what the headline metric can't. Here is the framework that gets scored highest.

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Next in this trackDesign an online experimentation (A/B testing) platform for ML models at scale.Next in this trackHow do you ensure end-to-end lineage and reproducibility for a production model (for debugging and audit)?Next in this trackWhen do you use batch, real-time (online), streaming, or async inference?
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