NVIDIA·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jul 2026

Summary

NVIDIA software engineer interview with a pretty meaty coding problem around JSON traversal. The question had a lot of moving parts and I don't think I covered everything cleanly, but it was an interesting problem to work through.

Questions Asked (1)

Given a deeply nested JSON document (roughly five levels deep), write code to traverse it and extract specific fields. Your solution needs to handle missing keys, arrays mixed with objects, and unknown nesting depth. Then compare a recursive approach to an iterative one, discuss time and space complexity, and talk through how you'd handle errors and validate the schema.

Algorithms & Data StructuresTechnical Trade-offsSystem Design

Author's notes

This is the kind of question that looks manageable until you actually start writing code.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and edge cases, then present a clean recursive solution with a generator or callback pattern, followed by an iterative version using an explicit stack. Compare trade-offs (recursion depth limits vs. manual stack management), analyze complexity, and discuss error handling and schema validation strategies.

Pro tip: Mention that recursion depth is bounded by nesting depth, not document size, and that an explicit stack can avoid Python's recursion limit for very deep documents. Also, emphasize that schema validation should be decoupled from traversal for maintainability.

1. Clarify requirements and edge cases

Ask about expected output format, handling of missing keys (skip, default, or error), and whether arrays can contain mixed types. Confirm if the schema is known or dynamic.

2. Design recursive solution

Write a recursive function that traverses objects and arrays, checks for key existence, and collects values. Use a helper to handle both dicts and lists uniformly.

3. Design iterative solution

Implement an explicit stack (or queue) to simulate recursion, pushing child nodes with their paths. This avoids recursion depth limits and gives more control over traversal order.

4. Compare approaches and analyze complexity

Discuss time O(N) where N is total nodes, and space O(D) for recursion (D = depth) vs. O(N) worst-case for iterative stack. Mention readability, performance, and Python recursion limit.

5. Discuss error handling and schema validation

Explain strategies: try/except for type errors, default values for missing keys, and using libraries like jsonschema or pydantic for validation. Emphasize separating validation from traversal.

Key Points to Mention

Handling missing keys with .get() or try/except, and using default values
Traversing mixed arrays and objects by checking isinstance()
Recursion depth limits and how iterative approach avoids them
Time complexity O(N) and space complexity O(D) for recursion vs O(N) for iterative
Schema validation using JSON Schema or pydantic, and when to validate
Error handling strategies: fail-fast vs. collect errors, and logging

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