Machine Learning Engineer Machine Learning Interview Questions
Practice 192 real Machine Learning interview questions for Machine Learning Engineer roles. From companies including Amazon, OpenAI, Snapchat, Apple, 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."
Normalize targets for multitask regression
You are training one machine learning model with a shared representation and two regression heads. Each example has two continuous labels: - Target A ...
Write self-attention and cross-entropy pseudocode
You are asked to explain core Transformer / deep learning components. Part A — Self-attention pseudocode Write clear pseudocode (not full code) for sc...
Design RL reward for speed limits
RL for Autonomous Driving — Conceptual + Practical You are training a reinforcement-learning agent to drive a vehicle. The interview moves from policy...
Explain ML and statistical modeling
Discuss the following machine learning and statistics topics: - In a supervised learning problem with severe class imbalance, what techniques would yo...
Implement Beam Search With Length Normalization
In a sequence generation model, you are given: - a start token <bos> - an end token <eos> - a maximum output length max_len - a beam size k - a functi...
Compare Unsupervised Clustering Methods
Explain several unsupervised clustering approaches and when you would use each one. At a minimum, compare centroid-based clustering, hierarchical clus...
Explain bias–variance, overfitting, and vanishing gradients
Answer the following ML fundamentals questions: 1. Bias–variance tradeoff: What are bias and variance? How do they relate to underfitting/overfitting?...
Explain dataset size, generalization, and U-Net skips
You are interviewing for an ML Engineer role in an image/video team. Answer the following conceptual questions clearly and concisely. 1) Small vs. lar...
Represent k-means as an MLP
Given fixed centroids q_1, ..., q_k and an input vector x, show how the nearest-centroid assignment step of squared-Euclidean k-means can be implement...
Build Premium User Propensity Model
Design an end-to-end modeling approach to identify free-tier users who are likely to convert to a premium subscription. Discuss: - the business object...
Build model to predict package delivery time
You are building an ML model to predict package delivery time (ETA) for shipments. Given historical shipping data (order created time, origin/destinat...
Design photo and listing quality models
Discuss how you would solve the following two machine learning product problems for a travel marketplace. 1. Improve booking performance by selecting ...
Compute Gaussian Probability and Regression Coefficients
You are given two independent standard normal random variables, X and Y. 1. Compute P[X > 3Y]. 2. In ordinary linear regression with design matrix X i...
How do you choose a model?
You are building machine learning features for a spreadsheet assistant. Explain how you would choose an appropriate model for a new problem. In your a...
Explain bias-variance and evaluate a classifier
You are interviewing for an Applied Scientist internship. Answer the following ML foundations questions. 1) Bias–variance - Define bias and variance i...
Explain Transformer Encoder and Decoder Behavior
Answer the following Transformer fundamentals questions in a machine learning interview: 1. What are the main differences between a Transformer encode...
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...
Implement attention and Transformer with backward pass
Implement Scaled Dot-Product Attention and a Transformer Block (No Autograd) Context: Build multi-head self-attention and a Transformer encoder-style ...
Model y from x and interpret distributions
Scenario You are given a dataset with one input feature x and a target y. The interviewer asks: “How would you model this?” Later, you are shown a plo...
Design Features for Residual Volatility
You have historical intraday data for a universe of equities. Design features and a modeling approach to predict a target stock's volatility over the ...