A user invokes their right to be forgotten. How do you delete their data across the whole ML stack?
Deleting a row is trivial. Removing a person's influence from embeddings, caches, derived datasets, and a trained model is not. GDPR and CCPA demand it regardless. Here is the plan that survives an audit.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Deleting a row is trivial. Removing a person's influence from embeddings, caches, derived datasets, and a trained model is not. GDPR and CCPA demand it regardless. Here is the plan that survives an audit.
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.
