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Meta·Software Engineer·Technical Phone Screen·Senior

Senior
May 2026

Summary

Meta Research Scientist coding screen with a simulation-style problem on a number line. Pretty straightforward setup but the edge cases kept me second-guessing myself the whole time.

Questions Asked (1)

Q1

You start at position 0 and want to reach a target position on a number line. Scooters are available at given positions (sorted ascending). You walk to the nearest scooter to your right, ride it for up to 10 units or until you hit the target, then repeat. Return the total distance covered while riding scooters (not walking).

Algorithms & Data Structures
Author's notes

Spent the first few minutes drawing it out on paper before touching any code, which I think saved me.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and edge cases, then outline a greedy simulation that tracks the current position and iterates through scooters. For each scooter, if it's ahead, walk to it, ride up to 10 units or until the target, and accumulate the riding distance. Finally, analyze time and space complexity.

Pro tip: Mention that you would confirm whether walking distance should be excluded and whether scooters can be reused; this shows attention to detail and avoids incorrect assumptions.

1. Clarify the problem

Ask about edge cases: target behind start, no scooters, multiple scooters at same position, and whether walking distance counts. Confirm that only riding distance is summed.

2. Outline the greedy simulation

Explain that you'll simulate the process: start at position 0, find the nearest scooter to the right, walk to it, then ride up to 10 units or until target, and repeat.

3. Walk through an example

Use a small example to demonstrate the logic, showing how you update the current position and accumulate riding distance.

4. Analyze complexity

State that the time complexity is O(n) where n is the number of scooters, as you iterate through the list once, and space complexity is O(1).

5. Discuss edge cases and optimizations

Mention handling of cases where the target is reached before using all scooters, or when scooters are behind the current position. Note that the sorted input allows linear scan.

Key Points to Mention

  • Greedy simulation approach
  • Tracking current position and remaining ride distance
  • Only summing riding distance, not walking
  • Handling edge cases: target behind start, no scooters, target reached mid-ride
  • Time complexity O(n) and space complexity O(1)
  • Using the sorted property of scooter positions for efficient iteration

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