Machine Learning Engineer Interview Questions
Practice 779 real interview questions for Machine Learning Engineer roles. From companies including Meta, OpenAI, Amazon, Snapchat, Google. Covers Coding & Algorithms, Machine Learning, ML System Design, Behavioral & Leadership.
"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 a Simplified DNS Resolver
Implement a simplified DNS resolver in Python. You are given an in-memory DNS zone and must complete a small resolver step by step. The goal is not to...
Explain Core ML Interview Concepts
Answer the following machine learning fundamentals questions in a phone screen for an applied scientist role: 1. What are the main assumptions of line...
Implement 1NN with NumPy
Implement a 1-nearest-neighbor classifier from scratch using NumPy. You are given: - X_train: a NumPy array of shape (n_train, d) containing training ...
Design a Double Descent Experiment
You are given a take-home assignment for a mechanistic interpretability or machine learning interview. Design an experiment that demonstrates sample-t...
Implement Backprop for a Tiny Network
Implement and explain the forward and backward pass of a small neural network using both NumPy and PyTorch tensors. Start with a batched input X of sh...
Design a Food Delivery Recommender
Design a recommendation system for a food delivery app similar to Uber Eats. When a user opens the home page, the system should recommend restaurants ...
Build a Payment Fraud Detection Model
You are interviewing for a Machine Learning Engineer role at a FinTech company. Part 1: Explain the following ML fundamentals: - What is overfitting? ...
Filter Bad Human Annotations
You are given a training dataset labeled by human annotators, but some annotations are low quality, inconsistent, rushed, adversarial, or simply wrong...
Build a Candidate Search System
Build an end-to-end candidate search system for recruiting. Input Each search request contains a job posting with: - Job title - Job description - Har...
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 annotators, ...
Debug a Broken Transformer
You are given a Transformer model implementation that does not train correctly. Describe how you would debug it systematically from data input to opti...
Design Duplicate File Detection
Design a system to find duplicate files. Start with a single-machine version: given a large directory tree, identify groups of files that have identic...
Compute Matrix Prefix Products And Gradients
You are given N square matrices A[0], A[1], ..., A[N-1], each of shape D by D. Define the inclusive prefix products: Y[i] = A[0] @ A[1] @ ... @ A[i] w...
Debug Transformer and Add KV Cache
You are given a small decoder-only transformer implementation for autoregressive language modeling. Part 1: Debugging The training code contains four ...
Improve Training With Noisy Annotators
You are given a labeled training dataset as a Pandas DataFrame. Each row contains features, an observed label, and an annotator identifier. The annota...
Explain and test completion-rate gaps
In a food delivery marketplace, alcohol-related orders have a lower order completion rate than non-alcohol orders. Answer the following: 1. Propose se...
Compare Losses and Explain LoRA
Answer the following machine learning fundamentals questions: 1. Compare mean squared error loss and cross-entropy loss. When is each appropriate, and...
Explain ranking cold-start strategies
You are interviewing for a machine learning engineer role focused on search, recommendations, or ranking. Discuss the following in the context of a la...
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...
Debug a broken Transformer implementation
You are given a small Transformer model implementation (e.g., in PyTorch) plus a tiny training script. The code executes, but the model does not match...