Amazon·Machine Learning Engineer·Technical Phone Screen·Senior

Senior

Jul 2026

Summary

Amazon ML Engineer coding round, got a classic interval merging problem dressed up in a conference room scheduling scenario. Pretty standard stuff but the edge cases around touching endpoints tripped me up a bit.

Questions Asked (1)

Given a list of potentially overlapping time intervals (as [start, end] pairs stored in arbitrary order), write a function that merges all overlapping or touching intervals and returns the smallest possible sorted list of non-overlapping intervals covering the same range.

Algorithms & Data Structures

Author's notes

My first instinct was to just sort by start time and walk through, which is the right move.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (e.g., input size, interval inclusivity, touching definition) and then propose a sort-based approach: sort intervals by start time, then iterate and merge overlapping or touching intervals into a result list. Discuss time and space complexity, and consider edge cases like empty input or single interval.

Pro tip: Mention that sorting is the key to achieving O(n log n) time, and explicitly state that you would handle touching intervals by checking if the next start is <= current end (or < if exclusive). This shows attention to detail and scalability, which Amazon values.

1. Clarify requirements and edge cases

Ask about input size, whether intervals are inclusive/exclusive, and if touching intervals should be merged. Confirm output format and sorting order.

2. Choose the algorithm

Propose sorting intervals by start time, then merging in a single pass. Explain why this is optimal (O(n log n) time) and simpler than alternatives like sweep line for this problem.

3. Walk through the merge logic

Describe iterating through sorted intervals, comparing each with the last merged interval, and merging if they overlap or touch. Otherwise, add the last merged interval to the result.

4. Analyze complexity and edge cases

State time complexity O(n log n) due to sorting, space O(n) for output. Discuss edge cases: empty list, single interval, all overlapping, no overlaps, and intervals with same start.

5. Provide code or pseudocode

Write clean code (e.g., Python) with clear variable names, handling edge cases, and possibly test with a small example to demonstrate correctness.

Key Points to Mention

Sorting intervals by start time is crucial for efficient merging.
Merge condition: next.start <= current.end (or < if exclusive) to handle touching intervals.
Time complexity: O(n log n) due to sorting; space complexity: O(n) for the result.
Edge cases: empty input, single interval, intervals fully contained within others, and intervals that touch exactly.
Use of a result list and updating the last interval's end when merging.
Potential follow-up: how to handle streaming intervals or very large datasets (external sorting).

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