Atlassian·Machine Learning Engineer·Technical Phone Screen·Senior

Senior

Jul 2026

Summary

Atlassian ML engineer interview, got a nested list problem that looked straightforward but had a twist on the weighting scheme. Took me a bit to realize the depth calculation was inverted compared to the standard version.

Questions Asked (1)

Given a nested list of integers, return the sum of all integers weighted by their depth, where deeper integers have LOWER weight (weight = max depth minus current depth). How would you approach this?

Algorithms & Data Structures

Author's notes

The classic version weights deeper integers more heavily, so I started going down that path before re-reading the prompt.

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AI HintsAI Generated

Suggested Approach

First, clarify the problem and edge cases, then explain a two-pass approach: compute the maximum depth, then recursively traverse the nested list, summing each integer multiplied by (maxDepth - currentDepth). Discuss time and space complexity, and consider iterative alternatives if recursion depth is a concern.

Pro tip: Mention that you can combine depth calculation and weighted sum in a single traversal by first finding the maximum depth, then doing a second pass—or use a post-order traversal that returns both depth and sum to avoid two passes. This shows you optimize for efficiency without sacrificing clarity.

1. Clarify the problem and constraints

Ask about input size, nesting depth limits, and whether the list can contain non-integer elements. Confirm the weight formula: weight = maxDepth - currentDepth.

2. Choose an approach

Decide between two-pass (find max depth, then sum) or one-pass (post-order traversal returning depth and sum). Explain trade-offs in time, space, and code complexity.

3. Outline the algorithm

Describe the recursive function: for each element, if integer, add value * (maxDepth - depth); if list, recurse with depth+1. For one-pass, return (maxDepth, weightedSum) from each call.

4. Analyze complexity and edge cases

State time O(n) and space O(d) for recursion, where n is total elements and d is max depth. Discuss empty list, single integer, deeply nested lists, and negative numbers.

5. Test with examples

Walk through a small example like [1,[4,[6]]] to verify the logic. If time permits, mention iterative BFS/DFS with stack to avoid recursion limits.

Key Points to Mention

Two-pass vs. one-pass traversal and their trade-offs
Recursive DFS with depth tracking
Time complexity O(n) and space complexity O(d)
Handling edge cases: empty list, single element, deep nesting
Iterative alternative using stack to avoid recursion depth issues
Clarifying the weight formula and confirming with the interviewer

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