Sliding Windowhard70 minAI/ML Engineer

Recommend Streaming Window Anomaly

AI/ML Engineer signal: sliding window + frequency map in a recommendation system context. This is a ProdMatch-owned ai ml engineer drill, framed as a April 2026 NVIDIA Personalization ML simulation, not a copied platform question.

Company context

NVIDIA · Personalization ML

Freshness

April 2026

Product surface

recommendation system

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

Question

For recommendation system, process a timestamp-ordered stream of candidates. Find the longest contiguous window where at most k distinct risk labels appear and the total severity stays under budget.

Input

Array of events {label, severity} and integers k, budget.

Output

Maximum window length satisfying both constraints.

Constraints

1 <= events.length <= 300000
1 <= k <= 50
Severity values are positive integers.

Concepts

vector search
RAG retrieval
recommendation graphs
sliding window
frequency map
stream processing

labels: A,B,A,C with k=2 and budget=7 -> longest valid window length is 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

Update the answer only after the window is valid.
Avoid recomputing the whole window on every move.

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