Your question is ML Project Architecture Choices. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Can you walk me through the most interesting machine learning project on your resume, and explain your architectural choices?
Choose one project and explain the problem, data, target, modeling pipeline, and the alternatives you considered. Cover feature processing, model training, evaluation methodology, production constraints, and how you validated that the architecture was appropriate. Be prepared to discuss failure modes, tradeoffs, and what you would change in a second iteration.