AI/ML Engineer signal: dynamic programming + knapsack in a feature store freshness context. This is a ProdMatch-owned ai ml engineer drill, framed as a March 2026 Dream11 ML Platform simulation, not a copied platform question.
Company context
Dream11 · ML Platform
Freshness
March 2026
Product surface
feature store freshness
ProdMatch interview simulation based on product-team patterns; not a claim of a real company question.
Your ML Platform roadmap has candidate improvements for feature store freshness. Each improvement has cost, lift and risk. Maximize lift under budget while keeping total risk below a threshold.
Input
Output
Constraints
Concepts
items [[2,5,1],[4,9,4]], budget=4, risk=4 -> 9
Try framing your own approach first. The 30 seconds you think before peeking is where learning happens.
Reveal the approach first.
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