Quora·Machine Learning Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say

Jun 2026

Summary

Quora ML Engineer interview with a coding round that was heavier on matrix manipulation than I expected. The rotation problem is the one that'll stick with me for a while.

Questions Asked (1)

Given an m×n matrix and a sequence of string commands, implement each command and return the resulting matrix. Commands include: 90° clockwise rotation, row swap, column swap, row reversal, and column reversal. The matrix is not necessarily square.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

The row/column swaps and reversals were fine, pretty mechanical.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Clarify the command semantics and matrix dimensions, then choose a representation that makes each operation efficient. Implement each command with careful index mapping, especially for rotation, and test with non-square matrices to ensure correctness.

Pro tip: For rotation, avoid creating a new matrix by using in-place techniques or index mapping; but if simplicity is preferred, a new matrix is acceptable—just discuss the trade-off. Also, consider pre-processing commands to combine consecutive operations for efficiency.

1. Clarify requirements and edge cases

Ask about command semantics (e.g., rotation direction, swap indices 0-based or 1-based), matrix dimensions, and whether commands can be chained. Confirm if in-place modification is required or if a new matrix is acceptable.

2. Choose data representation and operation strategies

Decide whether to store the matrix as a list of lists or a flat array. For each command, determine the most efficient approach: rotation may require transposition and reversal, swaps are straightforward, reversals can be done in-place.

3. Implement each command with index mapping

Write helper functions for each command. For rotation, map (i, j) to (j, m-1-i) for clockwise. For swaps, swap rows or columns. For reversals, reverse rows or columns in-place.

4. Test with non-square matrices and edge cases

Test with 1xN, Nx1, and rectangular matrices. Verify that rotation changes dimensions correctly. Check boundary conditions for swaps and reversals.

5. Analyze time and space complexity

Discuss the complexity of each operation: rotation O(m*n), swaps O(n) or O(m), reversals O(n) or O(m). Mention trade-offs between in-place and new matrix approaches.

Key Points to Mention

Handling non-square matrices: rotation changes dimensions, so track m and n carefully.
In-place vs. new matrix: trade-offs in space and simplicity.
Index mapping for rotation: (i, j) -> (j, m-1-i) for clockwise.
Command chaining: process sequentially, but consider optimizing by combining operations.
Edge cases: empty matrix, single row/column, multiple rotations.
Time complexity: O(m*n) for rotation, O(n) or O(m) for swaps/reversals.

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