Walk Through an ML Project

Prepare a deep dive on one machine learning project you have worked on. In a 60-minute interview, explain: - the problem statement and why it mattered - your specific role and ownership - the data, modeling approach, and methods you used - the main technical and product challenges - important tradeoffs you considered - how you measured success using offline metrics, online experiment metrics, and business metrics - what results the project achieved and what you would improve next Be ready for follow-up questions on why you chose certain metrics, how you handled ambiguity, and how you balanced model quality, system complexity, and business impact.