openai | | Interview Experience
Interview Date: Not specified
Result: Not specified
Difficulty: Not specified
Interview Process
The interview began with a debugging question related to a Transformer model, specifically focusing on a bug indicated in the code comments. The question was straightforward and engaging, although I also reviewed the driver code, which did not contribute significantly to solving the problem.
The follow-up involved a classifier problem that required training and evaluation, necessitating a discussion with the interviewer about various model modifications and trade-offs. Familiarity with the Transformer architecture was beneficial for this part of the interview.
The coding environment was slow, which made running code frustrating, so I tried to minimize the number of runs.
Technical Questions
- Debugging (Transformer model)
Tips & Insights
The prompts for the Human-Computer Interaction ML programming and Coding & Design Session interviews were vague, and there was limited information available. It may be helpful to exchange questions related to OpenAI (coding, backpropagation, retrieval-augmented generation), Explainable AI, and Anthropic (4-hour take-home, coding) for better preparation.