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Bit Manipulationhard70 minAI/ML Engineer

Vector Policy State Compression

AI/ML Engineer signal: bitmask DP + state compression in a vector search retrieval context. This is a ProdMatch-owned ai ml engineer drill, framed as a March 2026 Atlassian RAG Platform simulation, not a copied platform question.

Company context

Atlassian · RAG Platform

Freshness

March 2026

Product surface

vector search retrieval

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

Question

For vector search retrieval, each embeddings requires a subset of capabilities. Choose the smallest team of services covering all required capabilities; tie-break by lowest total risk.

Input

  • m capabilities and services with capability masks plus risk.

Output

  • Minimum service count and risk, or impossible.

Constraints

  • 1 <= m <= 22
  • 1 <= services.length <= 2000
  • Capability sets may overlap heavily.

Concepts

  • vector search
  • RAG retrieval
  • recommendation graphs
  • bitmask DP
  • state compression
  • subset enumeration

required={A,B,C}, services=[AB risk 4, C risk 1] -> count=2, risk=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

  • Do not shift beyond the integer width in fixed-width languages.
  • Keep feature-to-bit mapping stable.

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