ML engineering interviews care less about theory and more about how you build, deploy, and maintain models in production. These questions test that practical judgement.
ML SystemsModel DeploymentMLOpsData Pipelines
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Question 1
You are designing an ML pipeline for a fraud detection system that needs to score transactions in under 100ms. The interviewer asks how you would serve the model. What approach shows the best judgement?
