Openai·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Apr 2026Remote

Summary

OpenAI software engineer coding round. The problem seemed manageable at first but a late-stage requirement change completely invalidated the earlier approach, and the clock ran out before anything could be debugged.

Questions Asked (1)

GPU Credit allocation problem: given a set of GPU credit transactions, implement logic to track and deduct credits, with a follow-up requirement to process deductions in end-time order.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

Started fine, passed the first few test cases, then the last two revealed a whole new constraint: deductions had to happen in end-time order.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements: what constitutes a transaction, how credits are allocated and deducted, and what the follow-up means by 'end-time order'. Then design a data structure that supports efficient tracking and deduction, and discuss how to adapt it to process deductions in end-time order, considering trade-offs between time and space complexity.

Pro tip: Demonstrate awareness of real-world constraints: mention that in production systems, you'd need to handle concurrency, idempotency, and audit trails, and that the choice of data structure depends on the read/write patterns and scale.

1. Clarify requirements and assumptions

Ask questions to understand the transaction model: are credits allocated per user or globally? What are the fields of a transaction (e.g., start time, end time, amount)? What does 'deduct credits' mean in terms of ordering and validity? Confirm the follow-up: process deductions in end-time order.

2. Define data structures and operations

Propose a data structure to store transactions, such as a list or a priority queue keyed by end time. Outline operations: add transaction, deduct credits (possibly checking available balance), and process deductions in end-time order.

3. Design algorithm for initial requirement

Explain how to track and deduct credits as transactions arrive. For example, maintain a running balance and a list of active transactions; when deducting, iterate through transactions and subtract credits, ensuring no negative balance.

4. Adapt for end-time order processing

Modify the approach to process deductions in end-time order. Use a min-heap (priority queue) ordered by end time, or sort transactions by end time before processing. Discuss how this affects time complexity and whether online processing is required.

5. Analyze trade-offs and edge cases

Compare approaches: sorting vs. heap for end-time order, and discuss time/space complexity. Cover edge cases: insufficient credits, overlapping transactions, zero or negative credits, and concurrent access.

Key Points to Mention

Choice of data structure: priority queue (min-heap) for end-time order, or sorting if batch processing is acceptable.
Time complexity: O(n log n) for heap-based approach vs. O(n log n) for sorting, but heap allows online processing.
Handling insufficient credits: either reject the deduction, partially deduct, or queue for later.
Concurrency and atomicity: use locks or transactional semantics to avoid race conditions.
Idempotency: ensure deductions are not applied twice if the same transaction is processed multiple times.
Scalability: consider distributed systems and sharding if the number of transactions is large.

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