OpenAI Machine Learning Interview Questions
These are the 15 OpenAI machine learning interview questions AceOffer has reconstructed from candidate reports, sorted by how often each was reported. Transformer Debugging leads at 36×. Every question shows when it was last reported; the catalog refreshes monthly.
Key facts
- •15 distinct machine learning questions indexed
- •110 candidate reports across those questions
- •Most reported: Transformer Debugging — 36× (last seen April 2026)
- •Refreshed monthly · last updated August 2026
Which OpenAI rounds ask machine learning questions?
The OpenAI rounds below are where these questions come up. Counts are distinct questions, not times asked.
Most reported: Transformer Debugging — 36×
Which OpenAI machine learning questions get asked most?
Sorted by candidate-report frequency. Click any question for the full breakdown.
| Question | Round | Reported | Last seen |
|---|---|---|---|
| Transformer DebuggingFree Given a PyTorch implementation of a GPT-like causal transformer language model (nanoGPT-style), including a model class and a training loop, identify and… | Tech Deep Dive | 36× | April 2026 |
| ML Search / RAG System Design Design a Retrieval-Augmented Generation (RAG) system, typically framed as an enterprise-grade system that allows employees to ask questions over internal documents (similar… | Tech Deep Dive | 16× | March 2026 |
| ML Model Debugging A dedicated ML debugging round in OpenAI onsite interviews (MLE and Research roles). Candidates are given existing ML code containing intentional bugs… | Tech Deep Dive | 11× | July 2025 |
| Backpropagation An ML coding interview (typically 60–75 minutes) at OpenAI Research covering basic linear algebra and backpropagation. The 60-minute version uses Excalidraw (or… | Tech Deep Dive | 10× | March 2026 |
| Applied Statistics and Probability A 75-minute OpenAI Research onsite round that integrates probability theory, applied statistics, mathematical derivations, and Python/NumPy coding. The round is open-ended and… | Tech Deep Dive | 9× | March 2026 |
| Improve Tool / Image Recognition Model Training OpenAI has a product feature where users upload photos of real-world tools (e.g., hardware, equipment) and ask the model to identify them.… | Tech Deep Dive | 6× | December 2025 |
| LLM Decoding Stopping Time / Probability Distributions LLM inference time T has expected value E[T]=1. Multi-part: (1) Find P(T>5) using Markov inequality; (2) success rate with 1 restart within… | Tech Deep Dive | 5× | July 2026 |
| Matrix Cumulative Product with Hillis-Steele Scan Compute prefix/cumulative product of N × D×D matrices. (1) In-place with complexity analysis + why gradient fails; (2) Out-of-place forward & backward… | Tech Deep Dive | 4× | July 2026 |
| Human Annotation with High-Dimensional Input ML problem involving filtering annotator quality from labeled data. Given annotated dataset with binary labels from three classes of annotators (bad, mid,… | Tech Deep Dive | 4× | July 2026 |
| Multiprocessing / Distributed Neural Network Debugging Upcoming round. Candidate asking if this involves: concurrency bugs (race conditions, deadlocks, duplicate consumption) vs. distributed issues… | Tech Deep Dive | 3× | April 2026 |
| GPU Infrastructure and Kubernetes | Tech Deep Dive | 2× | August 2026 |
| ML Config / Configuration System | Tech Deep Dive | 1× | March 2026 |
| ML Fundamentals (Oral) | Tech Deep Dive | 1× | November 2025 |
| Building a Terraform Unknown infrastructure/provisioning question (candidate had never encountered before). Interviewer provided no feedback for 30 minutes, then indicated… | Tech Deep Dive | 1× | August 2026 |
| FP8/BF16 Mixed Precision Training & Numerical Overflow | Tech Deep Dive | 1× | April 2026 |
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