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."
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] =...
Optimize Nearest-Center Assignment Without Materializing NxKxD Distances
Given points X with shape N x D and cluster centers C with shape K x D, return an assignment for each point to its nearest center by L2 distance. The ...
Implement Backprop for a Tiny Network
This question evaluates understanding of backpropagation, gradient derivation, numerical stability of softmax cross-entropy, and practical implementat...
Explain ranking cold-start strategies
This question evaluates an engineer's competency in handling cold-start for users and items, constructing and applying content-based embeddings, organ...
LLM Fundamentals: Tokenization Design and KL-Regularized SFT
This question evaluates depth of knowledge in large language model fundamentals, specifically subword tokenization design and KL-regularized supervise...
Explain Sampled-Softmax Correction and Classification Loss Choice
A recommendation model must choose one item from a very large catalog. Training approximates the full softmax by sampling negative items from a nonuni...
Design a Double Descent Experiment
This question evaluates understanding of sample-wise double descent, experimental design for reproducible supervised-learning studies, and theoretical...
Explain Top-k and Top-p Decoding
This question evaluates understanding of autoregressive decoding strategies in probabilistic language models, assessing competency in reasoning about ...
Build a Payment Fraud Detection Model
This question evaluates a candidate's competency in applied machine learning for payment fraud detection, covering data preprocessing, temporal train/...
Evaluate Noisy Data for LLM Post-Training
This question evaluates competency in post-training data curation and experimental judgment for large language models, including assessing noisy datas...
Filter Bad Human Annotations
This question evaluates expertise in data quality and annotation filtering for machine learning, including annotator reliability modeling, noisy-label...
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 ...
Implement Grouped-Query Attention (GQA)
This question evaluates a candidate's understanding of transformer attention mechanisms, specifically how grouped-query attention balances the memory ...
Implement Masked Multi-Head Self-Attention
This question evaluates implementation and conceptual understanding of masked multi-head self-attention, covering scaled dot-product attention, separa...
Bias-Variance Tradeoff and Vanishing Gradients in Feedforward Networks
This question evaluates conceptual understanding of the bias-variance tradeoff and the vanishing-gradient problem in deep feedforward networks, two co...
Implement Focal Loss for Class-Imbalanced Classification
This question evaluates a candidate's ability to implement a specialized loss function for class-imbalanced classification from basic tensor operation...
Implement 1NN Embeddings and Forward Pass
This question evaluates proficiency in vectorized linear algebra and neural-network forward-pass implementation within the Machine Learning domain, co...
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 a Broken Transformer
This question evaluates proficiency in debugging and reconfiguring Transformer-based deep learning models, covering competencies in model internals (a...
Build a time-series forecasting model
Build a time-series forecasting model Forecast the Next H Steps for Time Series Context You are given one or more time series with timestamps and nume...