Machine Learning Engineer Machine Learning Interview Questions
Practice 217 real Machine Learning interview questions for Machine Learning Engineer roles. From companies including Amazon, OpenAI, Snapchat, Pinterest, TikTok.
"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 numerically stable masked cross-entropy in NumPy with label smoothing and optional temperature scaling. Validate shapes, dtypes, finite logi...
Self-Attention: Implementation, Complexity, and Efficient Variants
This question evaluates a machine learning candidate's understanding of the self-attention mechanism, including its implementation, computational comp...
Implement 1NN with NumPy
This question evaluates implementing a 1-nearest-neighbor classifier with NumPy, testing skills in vectorized numerical computation, distance metrics,...
Diagnose a Production Classifier and Defend Its Systems Design
Diagnose a Production Classifier and Defend Its Systems Design You own a binary classifier used by a downstream production service. The positive class...
Prevent Vanishing Gradients in Deep Networks
Prevent Vanishing Gradients in Deep Networks Clarifying Questions to Ask - Are we discussing feed-forward networks, recurrent networks, or both? - Sho...
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...
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...
Diagnose Strong Validation and Weak Production Performance
Diagnose Strong Validation and Weak Production Performance You are given a training repository for a model whose validation metric looks strong while ...
Answer an LLM Systems Quick-Fire Interview
You are given a rapid-fire LLM systems interview. Be prepared to explain Transformer architecture, attention and masking, multi-head attention, normal...
Reason About an Intercept Shift in Logistic Regression
Reason About an Intercept Shift in Logistic Regression A trained binary classifier produces p(x) = sigmoid(w^T x + b) and predicts the positive class ...
Implement Stable Sigmoid, Softmax, and Scaled Dot-Product Attention
Implement Stable Sigmoid, Softmax, and Scaled Dot-Product Attention Implement the mathematical core of three common neural-network operations without ...
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 ...
Machine Learning Fundamentals: Optimizers, Scaling Laws, and Clustering
This question evaluates conceptual grasp of core machine learning fundamentals: gradient-based optimizers, neural scaling laws, and unsupervised clust...
Explain Core ML Interview Concepts
You are in a phone screen for an applied scientist / machine-learning engineer role and are asked to verbally explain a set of machine-learning fundam...
Review a Compact GPT-Style Transformer Implementation
Review a Compact GPT-Style Transformer Implementation You are reviewing a compact decoder-only Transformer implementation intended for next-token lang...
Explain Transformer Internals and Implement Top-p Decoding
You are interviewing for an AI Scientist role. Explain the Transformer architecture in detail, including attention, positional encoding, encoder versu...
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...
Implement K-Means Without Numerical Libraries
Implement K-Means Without Numerical Libraries Implement K-means clustering for a list of finite numeric points using only core language features and e...
GRPO Deep Dive: Critic-Free RL, Parallelism, MLA, and Reward Design for a Reasoning LLM
This question assesses understanding of reinforcement learning algorithms used to post-train large reasoning language models, including critic-free po...
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...