Summary
I recently completed two online interviews with OpenAI, covering a coding challenge and a system design problem. I'm sharing my approaches to both to assist others in their preparation.
Full Experience
I recently completed two online interviews with OpenAI, and I felt they went quite smoothly. I'm sharing the details of the questions and my proposed solutions to help out other candidates preparing for similar roles. I anticipate the next stage will be the virtual onsite.
Interview Questions (2)
The problem involves managing GPU credits with additions, expirations, and costs, while maintaining temporal dependency. Unlike some common incorrect solutions that add all credits and deduct costs at the end, the correct approach requires simulating the process faithfully over time.
For each credit addition, say X credits at timestamp T_add expiring at T_expire, two entries should be created:
(T_add, X, 'add')(T_expire, X, 'expire')
For a cost operation of Y at timestamp T_cost, one entry is created:
(T_cost, Y, 'cost')
To calculate the balance, all entries are sorted by timestamp. The process then iterates through them:
'add'and'expire'operations directly adjust the current credit balance.- For a
'cost'operation, if the current credit balance is insufficient, return False. Otherwise, adjust future expire entries by deducting the cost from the earliest expiring credits first. For example, if 10 credits are spent and upcoming expires are(15, 7, 'expire')and(16, 6, 'expire'), the adjustment would be(15, 0, 'expire')and(16, 3, 'expire')(7 deducted from first, remaining 3 from second).
The problem requires designing a simple CI/CD pipeline with a linear, multi-step flow (not a Directed Acyclic Graph). The key is to ensure each step runs sequentially: once one step completes, the next one automatically begins.