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Graphshard70 minAI/ML Engineer

Batching Dependency DAG Recovery

AI/ML Engineer signal: topological sort + cycle detection in a model-serving batcher context. This is a ProdMatch-owned ai ml engineer drill, framed as a April 2026 Salesforce Inference Platform simulation, not a copied platform question.

Company context

Salesforce · Inference Platform

Freshness

April 2026

Product surface

model-serving batcher

ProdMatch interview simulation based on product-team patterns; not a claim of a real company question.

Question

You own model-serving batcher for a AI/ML Engineer loop. Given requests and directed dependencies between them, return a valid execution order. If a cycle exists, return an empty list and identify that the rollout is blocked.

Input

  • n nodes labelled 0..n-1 and dependency pairs [before, after].

Output

  • A valid order of all nodes, or [] when dependencies contain a cycle.

Constraints

  • 1 <= n <= 200000
  • 0 <= dependencies.length <= 400000
  • The graph may be disconnected.

Concepts

  • vector search
  • RAG retrieval
  • recommendation graphs
  • topological sort
  • cycle detection
  • dependency graph

requests: 4, deps: [[0,1],[0,2],[2,3]] -> [0,1,2,3] or [0,2,1,3]

Approach

Try framing your own approach first. The 30 seconds you think before peeking is where learning happens.

Clean Solution

Reveal the approach first.

How well did you understand?

Your rating tunes when this problem shows up again.

Common Mistakes

  • Mark visited when enqueueing, not after repeated dequeue.
  • Do not ignore disconnected components if the product surface can have them.

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