Machine Learning Interview Questions
Practice 628 real Machine Learning interview questions. From companies including Amazon, Meta, Google, TikTok, Uber. For roles like Data Scientist, Machine Learning Engineer, Software Engineer, Data Analyst.
"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 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...
Explain Logistic Regression, Backprop, and Adam
Answer the following machine learning fundamentals questions: 1. Logistic regression - Explain how logistic regression works for binary classificat...
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...
Evaluate Promotions for Uber Eats Users
Uber Eats wants to send promotions or coupons to users. Design an experiment and analysis plan to evaluate whether the promotion is effective. Address...
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...
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...
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...
Debug a GRPO training loop and explain ratios
You are given a simplified implementation of a GRPO (Group Relative Policy Optimization) training step for an RLHF-style policy model. The training is...
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...
Build cold-start restaurant ratings
Uber Eats wants a cold-start rating system for newly onboarded restaurants before they accumulate enough real reviews. You are asked to design the mod...
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 ...
Why do transformers struggle with long context?
In a transformer-based model, why is it difficult to process very long input context? Explain the main challenges in terms of computation, memory usag...
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...
Explain batch inference design
You need to generate predictions for a very large offline dataset, such as all users or all products, once per day using an already trained machine le...
Implement Masked Multi-Head Self-Attention
Implement the core self-attention module used inside a Transformer encoder. Given an input tensor X of shape (batch_size, sequence_length, d_model), f...
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 NumPy neural-network layers
You are given a neural-network coding task in NumPy. Let X be a batch input matrix of shape (B, d_in), W a weight matrix of shape (d_in, d_out), and b...
Design Features for Residual Volatility
You have historical intraday data for a universe of equities. Design features and a modeling approach to predict a target stock's volatility over the ...
Implement Streaming Clustering for Numbers
You receive a continuous stream of numeric values. Choose an appropriate clustering algorithm and implement it so that each incoming number can be ass...