Graphshard70 minAI/ML Engineer

Eval Evidence Path Finder

AI/ML Engineer signal: shortest path + weighted graph in a LLM evaluation harness context. This is a ProdMatch-owned ai ml engineer drill, framed as a May 2026 Paytm AI Quality simulation, not a copied platform question.

Company context

Paytm · AI Quality

Freshness

May 2026

Product surface

LLM evaluation harness

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

Question

In LLM evaluation harness, entities are connected by weighted evidence edges. For each query, find the least-cost evidence path from source to target while avoiding blocked entities.

Input

Weighted graph, blocked set, and q source-target queries.

Output

Minimum cost per query, or -1 if unreachable.

Constraints

1 <= nodes <= 100000
1 <= edges <= 300000
1 <= queries <= 100000
All weights are non-negative.

Concepts

vector search
RAG retrieval
recommendation graphs
shortest path
weighted graph
retrieval quality

0-1 cost 2, 1-2 cost 3, query 0->2 -> 5

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.

Next Similar Problems

Vector Dependency DAG Recoverymedium Vector Evidence Path Finderhard GraphRAG Dependency DAG Recoveryhard