← Amazon Interview Insights

Amazon·Software Engineer·Online Assessment (OA)·Junior

Junior
May 2026

Summary

Amazon SDE intern OA with a tricky optimization problem that looks straightforward until you actually try to code it up. The problem had a clever twist on splitting deliveries across warehouses to protect items from being discarded.

Questions Asked (1)

Q1

Given an array of n delivery sizes, distribute items into exactly k warehouses (deliveries can be split across warehouses but a warehouse can only hold items from one delivery) such that after discarding the k/2 warehouses with the most items, the total remaining items is maximized.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

I stared at this for a while before realizing the naive approach of just assigning deliveries directly was obviously suboptimal.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and objective, then propose an efficient algorithm such as dynamic programming or greedy with sorting. Discuss trade-offs between time and space complexity, and validate with examples.

Pro tip: Demonstrate Amazon's leadership principles by emphasizing customer obsession (maximizing remaining items) and ownership (considering edge cases like k > n).

1. Understand the problem

Restate the problem in your own words, ask clarifying questions about constraints (e.g., n, k, item sizes) and confirm the objective.

2. Explore approaches

Brainstorm potential algorithms (e.g., DP, greedy, binary search) and discuss their feasibility and complexity.

3. Design the algorithm

Select the most efficient approach, outline steps, and justify why it works for all cases.

4. Analyze complexity

Compute time and space complexity, and discuss possible optimizations.

5. Test with examples

Walk through small examples and edge cases to verify correctness.

Key Points to Mention

  • Sorting the array to facilitate grouping
  • Dynamic programming for optimal partitioning
  • Greedy approach with proof of correctness
  • Time and space complexity trade-offs
  • Edge cases: k > n, k odd, large n
  • Amazon leadership principles: customer obsession, ownership

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.