Pinterest Machine Learning Engineer Interview Questions
Practice the exact questions companies are asking right now.
"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."
"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 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?...
Design a real-time home feed ranker
Scenario Design a real-time home feed (e.g., social or content platform) that is responsive to user engagement. Users open the app and see a ranked li...
Generate all hyperparameter combinations
You are given several groups of hyperparameter choices for an ML experiment. Each group contains one hyperparameter name and a list of candidate value...
Implement string-based rounding without floats
Coding You are not allowed to parse the input into a built-in floating type (to avoid overflow and precision issues). Work directly on strings. 1) Imp...
Design an unsafe content detection system
Scenario You are building a system that detects and mitigates unsafe user-generated content (UGC) on a large platform. Unsafe content can include: hat...
Solve a 9x9 Sudoku puzzle
Given a partially filled 9×9 Sudoku board, fill the empty cells so that the completed board is valid. A valid Sudoku satisfies: - Each row contains di...
Support room moves and query top-k fastest
Problem There are R rooms labeled 0..R-1 (in increasing order), and P people labeled 0..P-1. - Initially, all people are in room 0. - Operation move(p...
Implement trie-based autocomplete
Problem Design an autocomplete data structure using a trie. You must support: 1. insert(word: string) -> void 2. search(word: string) -> bool (exact m...
Design an ads system to improve CTR
Design an ML system to increase the click-through rate (CTR) of ads shown in the feed of an online social media platform. Address the following: 1. Go...
Explain overfitting and how to prevent it
You are asked rapid-fire ML fundamentals questions. 1. What is overfitting? Explain it in terms of training vs. validation performance and generalizat...
Explain learning-rate fluctuation and vanishing gradients
ML Fundamentals Answer the following conceptual questions: 1. Learning rate vs. training stability: Why can training metrics (loss/accuracy) fluctuate...