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Airbnb·Machine Learning Engineer·Technical Phone Screen·Senior

Senior
Jun 2026

Summary

Airbnb ML engineer coding screen, one question but it had real depth with two follow-ups that caught me off guard. The base problem looked easy and I almost underestimated it.

Questions Asked (1)

Q1

Parse a URL query string into a dictionary, handling keys with no value, repeated keys, percent-encoded characters, and malformed inputs.

Algorithms & Data StructuresTechnical Trade-offsAPI & Integrations
Author's notes

The base case took maybe five minutes and I felt good about it.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and edge cases, then outline a parsing algorithm that splits on '&' and '=', decodes percent-encoded characters, and handles repeated keys by storing values in a list. Discuss trade-offs between using built-in libraries versus manual parsing, and how to handle malformed inputs gracefully.

Pro tip: Mention that in production ML systems, query strings often come from tracking parameters or API calls, so robustness to malformed input and consistent decoding (e.g., '+' as space) is critical; showing awareness of real-world data quirks impresses interviewers.

1. Clarify requirements and edge cases

Ask about expected behavior for missing values, repeated keys, encoding standards (e.g., application/x-www-form-urlencoded), and malformed inputs. Confirm whether to use built-in libraries or implement manually.

2. Design the parsing algorithm

Outline steps: split query string by '&', then each pair by '='. For each key-value pair, percent-decode both key and value, and handle missing '=' by treating value as empty string or None.

3. Handle repeated keys and data structures

Decide on dictionary structure: map each key to a list of values to preserve order and duplicates. Discuss alternatives like last-value-wins and justify your choice based on use case.

4. Address malformed inputs and encoding

Explain how to handle invalid percent-encoding (e.g., '%' not followed by two hex digits) by either raising an error or skipping/repairing. Mention decoding '+' as space for form-encoded data.

5. Discuss trade-offs and testing

Compare manual parsing vs. using urllib.parse.parse_qs. Highlight performance, security (e.g., injection), and maintainability. Suggest test cases for edge cases like empty string, '&&', '=', and encoded characters.

Key Points to Mention

  • Use of standard libraries like urllib.parse.parse_qs for correctness and security, but be prepared to implement manually if required.
  • Handling of repeated keys by storing values in a list, and the trade-off with last-value-wins.
  • Percent-decoding rules: decode %XX sequences, and treat '+' as space in application/x-www-form-urlencoded.
  • Malformed input handling: strategies for invalid encoding, missing '=', and empty segments.
  • Edge cases: empty query string, keys without values, multiple '=' in a value, and non-ASCII characters.
  • Performance considerations for large query strings and potential security implications (e.g., denial of service via deeply nested encoding).

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