OpenAI Machine Learning Engineer Machine Learning Interview Questions
Practice 20 real Machine Learning interview questions for Machine Learning Engineer roles at OpenAI.
"I got asked a hardcore MCM DP question and I saw it on PracHub as well. Solved that question in 5 minutes. Without PracHub I doubt I could solve it in 5 hours. Though somehow didn't get hired, perhaps I guess I solved it too fast? /s"
"Believe me i'm a student here jn US. Recently interviewed for MSFT. They asked me exact question from PracHub. I saw it the night before and ignored it cause why waste time on random sites. I legit wanna go back and redo this whole thing if I had chance. Not saying will work for everyone but there is certainly some merit to that website. And i'm gonna use it in future prep from now on like lc tagged"
"10 years of experience but never worked at a top company. PracHub's senior-level questions helped me break into FAANG at 35. Age is just a number."
"I was skeptical about the 'real questions' claim, so I put it to the test. I searched for the exact question I got grilled on at my last Meta onsite... and it was right there. Word for word."
"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."
"I've used LC, Glassdoor, and random Discords. Nothing comes close to the accuracy here. The questions are actually current — that's what got me. Felt like I had a cheat sheet during the interview."
"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."
"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."
"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."
"Literally just signed a $600k offer. I only had 2 weeks to prep, so I focused entirely on the company-tagged lists here. If you're targeting L5+, don't overthink it."
"Coaches and bootcamp prep courses cost around $200-300 but PracHub Premium is actually less than a Netflix subscription. And it landed me a $178K offer."
"I honestly don't know how you guys gather so many real interview questions. It's almost scary. I walked into my Amazon loop and recognized 3 out of 4 problems from your database."
"Discovered PracHub 10 days before my interview. By day 5, I stopped being nervous. By interview day, I was actually excited to show what I knew."
"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."
"The search is what sold me. I typed in a really niche DP problem I got asked last year and it actually came up, full breakdown and everything. These guys are clearly updating it constantly."
Implement Masked Cross-Entropy with Label Smoothing
Implement Masked Cross-Entropy with Label Smoothing You are given a NumPy array of unnormalized class logits with shape (B, C), integer labels with sh...
Implement 1NN with NumPy
This question evaluates implementing a 1-nearest-neighbor classifier with NumPy, testing skills in vectorized numerical computation, distance metrics,...
Compute entropy and implement 1-NN
You are given two short ML coding problems from a machine-learning engineer screen. Both are implementation-focused but probe whether you understand t...
Debug MiniGPT and Backpropagate Matmul
This is a hands-on PyTorch screen with two independent tasks. You share a code editor with the interviewer and are expected to run the code, read trac...
Improve Training With Noisy Annotators
You are given a labeled training dataset as a Pandas DataFrame. Each row contains feature columns, an observed label, and an annotator_id identifying ...
Derive Sharded Matrix Multiplication and Backpropagation
Derive Sharded Matrix Multiplication and Backpropagation Consider Y = X @ W, where X has shape (B, D) and W has shape (D, H). Training runs on P devic...
Compute Matrix Prefix Products And Gradients
You are given $N$ square matrices $A[0], A[1], \dots, A[N-1]$, each of shape $D \times D$. Define the inclusive prefix (cumulative) products: $$Y[i] =...
Implement Backprop for a Tiny Network
This question evaluates understanding of backpropagation, gradient derivation, numerical stability of softmax cross-entropy, and practical implementat...
Filter Bad Human Annotations
This question evaluates expertise in data quality and annotation filtering for machine learning, including annotator reliability modeling, noisy-label...
Improve classifier with noisy multi-annotator labels
Problem You are given a text dataset for a binary classification task (label in $\{0,1\\}$). Each example has been labeled by multiple human annotator...
Debug a Broken Transformer
This question evaluates proficiency in debugging and reconfiguring Transformer-based deep learning models, covering competencies in model internals (a...
Defend a Research Direction and Experiment Design
You are interviewing for a research-focused Machine Learning Engineer role at a frontier AI lab. The onsite includes a collaboration / research-discus...
Debug Transformer and Add KV Cache
This question evaluates debugging and implementation skills for transformer-based autoregressive language models, focusing on attention mechanics, pos...
Debug a broken Transformer implementation
You are given a small Transformer model implementation (e.g., in PyTorch) plus a tiny training script. The code executes, but the model does not match...
Derive Backpropagation for Matrix-Product Layers
Consider a neural-network block whose output is produced by multiplying a sequence of trainable weight matrices together, then applying the resulting ...
Debug transformer and train classifier
Debug and Fix a Transformer Text Classifier, Then Train and Evaluate It You inherit a small codebase for a transformer-based text classifier. It ships...
Debug a transformer training pipeline
Debug a Transformer training pipeline You are handed a PyTorch Transformer encoder–decoder training pipeline that misbehaves. The pipeline includes to...
Diagnose Transformer training and inference bugs
Debugging a Transformer That Intermittently Throws Shape/Dtype Errors and Fails to Converge You inherit a Transformer-based sequence model (decoder-on...
Train a classifier and analyze dataset
End-to-End Binary Classifier Workflow (EDA → Modeling → Fairness → Report) You are given a labeled tabular dataset and asked to implement a reproducib...
Build and troubleshoot image classification and backprop
Build and troubleshoot image classification and backprop CIFAR-like Noisy Dataset: Baseline, Data Quality Plan, and First-Principles Backprop Context:...