ML lifecycle, roles, team topology + DSA Adv Graphs

Interview questions to prep

1. Pick between Dijkstra, Bellman-Ford, Floyd-Warshall, MST (Prim/Kruskal), or topo sort — defend the choice.
2. What does this problem assume about edge weights (non-negative? integer? bounded?) — and what breaks if those don't hold?
3. Walk me through complexity in V and E, and the data-structure choice (heap vs Fibonacci heap vs array).

Interview questions to prep

1. Pick between Dijkstra, Bellman-Ford, Floyd-Warshall, MST (Prim/Kruskal), or topo sort — defend the choice.
2. What does this problem assume about edge weights (non-negative? integer? bounded?) — and what breaks if those don't hold?
3. Walk me through complexity in V and E, and the data-structure choice (heap vs Fibonacci heap vs array).

Interview questions to prep

1. Walk through the end-to-end ML lifecycle and the failure modes at each stage.
2. Where do most ML projects actually fail in the lifecycle, and what catches it earlier?

Interview questions to prep

1. Compare the responsibilities of an ML researcher vs an MLE vs an MLOps engineer.
2. When does a company actually need a dedicated ML platform team — and what's the smallest valid platform?

Interview questions to prep

1. How would you structure an ML team at a 50-person startup vs a 5,000-person company?
2. Where do ownership disputes typically erupt between data, ML, and platform teams — and how do you preempt them?