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Openai·Software Engineer·Technical Phone Screen·Senior

SeniorPass
Jun 2026Remote

Summary

Interviewed with OpenAI's Infra Inference team for a software engineering role. It was a 75-minute technical phone screen focused entirely on implementing malloc from scratch, which was more involved than I expected but went well enough to pass.

Questions Asked (1)

Q1

Implement malloc and free from scratch, then optimize your solution.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

Started with a linear scan first-fit approach, which took me maybe 25 minutes.

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AI HintsAI Generated

Suggested Approach

Start by clarifying assumptions (e.g., single-threaded, no coalescing initially) and implement a simple free list allocator with malloc and free. Then iteratively optimize by adding splitting, coalescing, segregated free lists, and possibly a slab allocator for small sizes, discussing trade-offs at each step.

Pro tip: Demonstrate awareness of real-world allocator design by mentioning alignment, fragmentation, and performance metrics; also discuss how you would test and benchmark your allocator against system malloc.

1. Clarify Requirements and Constraints

Ask about the environment: single-threaded vs multi-threaded, expected allocation sizes, performance goals, and whether alignment or debugging features are needed.

2. Design Basic Allocator

Implement a simple free list allocator using a linked list of free blocks, with malloc finding a suitable block and free adding it back. Include metadata for block size and status.

3. Add Core Optimizations

Introduce splitting to reduce internal fragmentation and coalescing to reduce external fragmentation. Consider boundary tags for efficient coalescing.

4. Advanced Optimizations

Implement segregated free lists (size classes) for faster allocation, and a slab allocator for small objects to reduce overhead. Discuss trade-offs like memory overhead vs speed.

5. Evaluate and Iterate

Benchmark against system malloc using metrics like throughput, fragmentation, and memory utilization. Discuss further optimizations like thread-local caches or lock-free structures if needed.

Key Points to Mention

  • Memory alignment and metadata overhead
  • Fragmentation (internal and external) and mitigation strategies
  • Splitting and coalescing of free blocks
  • Segregated free lists and size classes
  • Slab allocation for small objects
  • Thread safety and performance trade-offs

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