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Ziprecruiter·Machine Learning Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Phone screen for an MLE role at Ziprecruiter. The coding problem was split into three parts and the prompt was long, so time management was a real factor. Conceptually not brutal, but you can lose time fast if you're not careful about how you structure things.

Questions Asked (1)

Q1

Given a list of objects where each has a string ID and other properties, implement functions to retrieve the next and previous ID for a given ID.

Algorithms & Data Structures
Author's notes

The prompt was way longer than the actual difficulty warranted, which threw me off a bit at first.

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AI HintsAI Generated

Suggested Approach

Clarify the requirements first: whether the list is static or dynamic, and if the IDs are ordered. Then propose an efficient solution using a hash map to store ID-to-index mappings, enabling O(1) next/previous lookups, and discuss trade-offs for dynamic updates.

Pro tip: Mention that if the list is static, you can precompute a mapping from each ID to its next and previous IDs, making lookups O(1) with O(n) space. Also, consider edge cases like first/last elements and non-existent IDs.

1. Clarify requirements

Ask about the list's mutability, ID uniqueness, ordering, and expected operations. Confirm whether next/previous should wrap around or return null at boundaries.

2. Choose data structures

For static lists, use a hash map from ID to index or precomputed next/prev pointers. For dynamic lists, consider a doubly linked list combined with a hash map for O(1) updates.

3. Implement core functions

Write functions getNextID(id) and getPrevID(id) that look up the ID in the map and return the adjacent ID, handling edge cases.

4. Analyze complexity

State time and space complexity: O(1) lookup time with O(n) space for the map. Discuss trade-offs if using a linked list for dynamic updates.

5. Test with examples

Walk through examples including first, last, middle, and non-existent IDs to demonstrate correctness and edge-case handling.

Key Points to Mention

  • Hash map for O(1) ID lookup
  • Precomputed next/previous pointers for static lists
  • Doubly linked list for dynamic lists with O(1) insert/delete
  • Edge cases: first/last element, non-existent ID, empty list
  • Time and space complexity trade-offs
  • Handling duplicate IDs or unordered lists

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