Instacart·Machine Learning Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Jun 2026

Summary

Coding screen for an ML Engineer role at Instacart. Just the one problem but they pushed for the optimal solution, so be ready to go beyond the brute force.

Questions Asked (1)

Given a sorted array of integers (possibly with negatives), return a new array of the squared values in non-decreasing order. Can you do it in O(n) time?

Algorithms & Data Structures

Author's notes

I knew the naive version immediately, square everything and sort, but they wanted O(n) and I fumbled around for a bit before landing on the two-pointer idea.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and constraints, then propose a two-pointer approach that leverages the sorted order to compare absolute values from both ends, filling the result array from the end to achieve O(n) time. Walk through a small example to validate the logic, and discuss edge cases and complexity.

Pro tip: Mention that this is a common pattern for sorted arrays with negatives, and relate it to how you'd handle similar problems in ML pipelines (e.g., feature scaling or distance computations). This shows you think about efficiency in real-world ML contexts.

1. Clarify and Confirm

Restate the problem to ensure understanding: sorted array, possibly negative, return squares in non-decreasing order. Ask about input size, duplicates, and whether in-place is allowed.

2. Brute Force vs Optimal

Acknowledge the naive O(n log n) approach (square then sort) and explain why it's suboptimal. Then introduce the two-pointer technique to achieve O(n).

3. Two-Pointer Strategy

Use left and right pointers at the ends of the array. Compare absolute values, place the larger square at the end of the result array, and move the corresponding pointer inward.

4. Walk Through Example

Trace the algorithm on a small example like [-4, -2, 0, 1, 3] to demonstrate correctness and pointer movement.

5. Complexity and Edge Cases

State O(n) time and O(n) space (for output). Discuss edge cases: all negatives, all positives, empty array, single element, duplicates.

Key Points to Mention

Two-pointer technique from both ends
Comparing absolute values to determine larger square
Filling result array from the end to avoid shifting
Time complexity O(n) and space complexity O(n)
Handling negative numbers and zeros
Edge cases: empty array, single element, all negatives/positives

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