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Meta·Software Engineer·Onsite - Coding / Algorithms·Intermediate

Intermediate
May 2026

Summary

Meta SWE onsite coding round. One algorithm problem, implement a solution in Python or whatever language you prefer. Pretty standard setup but the problem itself had some specific constraints worth knowing about.

Questions Asked (1)

Q1

Implement an algorithm to solve the '361' problem, which involves specific constraints around bytecode or similar low-level requirements.

Algorithms & Data Structures
Author's notes

The problem description was a bit cryptic going in.

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AI HintsAI Generated

Suggested Approach

First, clarify the '361' problem constraints and expected input/output, as the description is ambiguous. Then, outline a solution that handles low-level bytecode or memory constraints, focusing on efficiency and correctness. Discuss trade-offs and potential optimizations.

Pro tip: Demonstrate familiarity with Meta's emphasis on scalable systems by discussing how your solution would perform under heavy load and how you'd test edge cases.

1. Clarify the Problem

Ask clarifying questions to understand the exact constraints, input format, and expected output of the '361' problem. Confirm whether it involves bytecode manipulation, memory limits, or specific algorithmic challenges.

2. Outline a High-Level Approach

Describe the overall strategy, such as using a specific data structure or algorithm that meets the low-level requirements. Mention any assumptions and why they are reasonable.

3. Detail the Algorithm

Walk through the steps of your algorithm, explaining how it handles the constraints. Use pseudocode or clear verbal description, focusing on efficiency and correctness.

4. Analyze Complexity and Trade-offs

Discuss time and space complexity, and any trade-offs made (e.g., speed vs. memory). Explain how your solution scales and potential bottlenecks.

5. Test and Validate

Propose test cases, including edge cases, and explain how you would verify the solution's correctness and performance.

Key Points to Mention

  • Understanding of bytecode or low-level memory management
  • Algorithmic efficiency and complexity analysis
  • Handling edge cases and constraints
  • Scalability and performance under load
  • Testing strategies and validation
  • Trade-offs between different approaches

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