TikTok·Machine Learning Engineer·Technical Phone Screen·Senior

Senior

Jun 2026

Summary

TikTok ML engineer round that was basically a deep-dive into one hard geometry/algorithm problem. They wanted a full working solution plus complexity analysis and edge case handling, not just a sketch. Felt more like a systems-adjacent coding round than a pure ML interview.

Questions Asked (1)

Given n axis-aligned rectangular buildings each described by a left x-coordinate, right x-coordinate, and height, compute the outer silhouette (skyline) of all buildings combined. Return the list of critical points where the height changes, sorted by x, with no two consecutive points at the same height, and the last point dropping to zero. Aim for O(n log n) time. Implement an efficient approach such as a sweep line with a max-heap or divide-and-conquer, and explain your design. Also specify how you handle ties when multiple building edges share the same x-coordinate: entering edges before leaving, among entering edges process taller buildings first, among leaving edges process shorter buildings first. Discuss correctness, complexity, and edge cases including identical buildings, fully nested intervals, buildings that share a border, and very large coordinate values.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

This is the classic skyline problem but they pushed way further than I expected.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and constraints, then propose a sweep line algorithm with a max-heap to track active building heights in O(n log n) time. Explain the event processing order (entering before leaving, taller entering first, shorter leaving first) and how to generate critical points by comparing the current max height to the previous. Finally, discuss correctness, complexity, and edge cases.

Pro tip: Mention that you can avoid heap deletion by using lazy removal: when processing a leaving edge, mark the height as inactive and pop from the heap until the top is active. This keeps the heap operations O(log n) and simplifies the code.

1. Clarify and Define

Restate the problem, confirm input format, and define critical points. Ask about tie-breaking rules if not specified.

2. Choose Algorithm

Propose a sweep line with a max-heap (or divide-and-conquer) and justify O(n log n) time. Explain why a naive approach is inefficient.

3. Detail Event Processing

Describe how to create events (x, type, height) and sort them with the specified tie-breaking order. Explain how to update the heap and track the current max height.

4. Generate Skyline

Explain how to output critical points: after each event, if the max height changes, add the point (x, new height). Ensure no consecutive points have the same height and the last point is (max_x, 0).

5. Analyze and Test

Discuss correctness (invariant: heap contains active heights), complexity (O(n log n) time, O(n) space), and edge cases (identical buildings, nested intervals, shared borders, large coordinates).

Key Points to Mention

Sweep line algorithm with events for building start and end, sorted by x-coordinate with tie-breaking rules.
Max-heap to maintain active building heights, with lazy deletion to handle removals efficiently.
Critical point generation: compare current max height with previous max height after each event.
Tie-breaking order: entering before leaving, taller entering first, shorter leaving first.
Time complexity O(n log n) due to sorting and heap operations; space complexity O(n).
Edge cases: identical buildings, fully nested intervals, buildings sharing a border, very large coordinates (use 64-bit integers).

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