Amazon Machine Learning Engineer Machine Learning Interview Questions
Practice 34 real Machine Learning interview questions for Machine Learning Engineer roles at Amazon.
"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."
Explain XGBoost Parallelism Strategies
Explain How XGBoost Parallelizes Training Scope Describe how XGBoost achieves parallelism: 1. Within a single machine - Histogram-based split findi...
Explain imbalance, metrics, bias-variance, Transformers vs. CNNs
Question You are given a highly imbalanced binary classification problem in a fraud-detection setting (roughly 1% positives). Walk through the core ML...
Test whether two user populations differ
Problem You are given two groups of users: - Group A: North America users - Group B: Europe users Each user has a vector of continuous features (e.g.,...
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...
Analyze attention complexity and improvements
This question evaluates understanding of Transformer self-attention in the Machine Learning domain, testing the ability to analyze time and space comp...
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 core components of reinforcement learning
In reinforcement learning, we model an agent that interacts with an environment over time. The agent observes the state of the environment, takes acti...
Explain key ML theory and techniques
Explain key ML theory and techniques This Amazon Machine Learning Engineer onsite covers a breadth of core ML theory and applied modeling. Be ready to...
Explain Collaborative Filtering Approaches
Collaborative Filtering for Recommendations: Approaches, Losses, Regularization, Cold Start, Bias, Evaluation, and Scale Context You are designing a r...
Explain core ML fundamentals
Explain core ML fundamentals ML Fundamentals — Onsite Interview Task Context: Answer the following fundamentals as if in an onsite ML Engineer intervi...
Design a search relevance prediction approach
This question evaluates competency in machine learning for search relevance, including relevance modeling, feature engineering across lexical, semanti...
Explain modern modeling and alignment methods
This question evaluates mastery of modern model architectures and alignment techniques—covering attention optimizations like FlashAttention, parameter...
Compare float types and design ablation
This question evaluates understanding of floating-point numerical representations and experimental design for ablation studies, testing competencies i...
Explain weight initialization methods and goals
This question evaluates a candidate's understanding of weight initialization in deep neural networks, assessing competencies in training dynamics such...