Write down the SVM dual, and explain what the Lagrange multipliers and KKT conditions tell you.
Most candidates can recite 'maximize the margin'. The dual is where you prove you really understand why only support vectors matter and where the kernel trick originates. Here is the derivation an interviewer wants.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Most candidates can recite 'maximize the margin'. The dual is where you prove you really understand why only support vectors matter and where the kernel trick originates. Here is the derivation an interviewer wants.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
