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."
Design a search relevance prediction approach
Search relevance prediction You are asked to predict relevance for an e-commerce search engine (given a user query and a product/document). Prompt 1. ...
Explain Core ML Fundamentals
Answer these machine-learning fundamentals questions clearly and precisely: 1. Logistic regression: why is it suitable for binary classification, and ...
Design a house-price prediction workflow
Design a house-price prediction workflow Predicting Home Sale Prices: End-to-End ML Design Context You have historical home-sale records with features...
Explain 3D geometry data
Explain 3D geometry data 3D Geometry Data: Representations, Preprocessing, Modeling, and Serving Prompt You are working with 3D geometry data in ML pi...
Explain LLM fundamentals and trade-offs
Explain LLM fundamentals and trade-offs LLM Fundamentals — Onsite Interview Task Context: Assume a modern transformer-based LLM. Provide precise, conc...
Derive and implement calibration via temperature scaling
Derive and implement calibration via temperature scaling Temperature Scaling for Softmax Calibration Context You have a trained multi-class classifier...
Explain overfitting, imbalance, undersampling, and attention heads
Explain overfitting, imbalance, undersampling, and attention heads Context You are designing and evaluating production machine learning models, with e...
Compare float types and design ablation
Floating-point types and ablation study design You are training deep neural networks on modern accelerators that support multiple floating-point forma...
Compare decision trees and random forests
Compare decision trees and random forests. In your answer, discuss: - How a single decision tree is built and its main advantages and disadvantages. -...
Explain vanishing gradients and activations
Explain the vanishing gradient problem in deep neural networks. In your answer: - Describe how backpropagation works at a high level and why gradients...
Explain ML evaluation, sequence models, and optimizers
Scenario An interviewer is deep-diving into an ML project you built (you can assume it is a supervised model unless specified otherwise). They want yo...
Design approach for class imbalance
Design approach for class imbalance Imbalanced Binary Classification: Learning, Evaluation, and Model Selection Context You are training a binary clas...