Your question is Integrate Datasets for ML Workflows. 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).
You're working on shared ML infrastructure and need a pipeline approach that supports collaboration across research, data science, and infrastructure teams. The work spans dataset ingestion, validation, feature preparation, training workflow execution, and deployment handoffs.
How would you integrate datasets and deploy efficient ML workflows with researchers, data scientists, and infrastructure teams?