Uber Machine Learning 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."
"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 linear and logistic regression
Explain and implement linear regression and logistic regression from scratch. Your answer should cover: - The prediction function for each model - The...
How would you design an ETA prediction system?
Design an end-to-end ETA (Estimated Time of Arrival) system for a maps / ride-hailing / delivery product. Assume users request an ETA for a trip from ...
Implement convex minimization on an interval
Task: Minimize a Black-Box Convex Function on [a, b] Using Only Function Evaluations Context You are given a real-valued, convex function F(x) defined...
Design ETA prediction for Uber rides
System Design: Real‑Time Pickup and Drop‑off ETA Prediction Context: You’re designing an end‑to‑end system that predicts pickup and drop‑off ETAs at t...
Implement 1D convex minimization in Python
1D Black-Box Convex Minimization (Gradient-Free) Task Implement in Python an algorithm to minimize a 1D convex function F(x) over a closed interval [a...
Build and assess CTR prediction
CTR Prediction with Delayed Feedback and Extreme Class Imbalance You are building a model to predict the probability that an ad impression results in ...
Diagnose location-sorted recommender causing revenue drop
Eats recommendations were changed to rank items primarily by distance to the user; after launch, add-to-cart rate rose but revenue per session fell. D...
Select the better $5 promo-targeting model
Coupon Targeting Under a Daily Budget: Policy, OPE, Calibration, and Monitoring Context - You have two user-scoring models for a $5 coupon: M0 (curren...
Build and deploy an uplift targeting model
Uplift Modeling and Policy Design for Free Trial/Bonus Targeting You ran a past randomized test that offered some users a free trial/bonus (treatment)...
Explain XGBoost depth, regularization, and dropout
ML Conceptual Questions (Onsite) Answer the following: (a) Gradient-boosted decision trees: How does maximum tree depth affect bias/variance, overfitt...
Implement Multi-Head Self-Attention
Implement a multi-head self-attention module in PyTorch without using torch.nn.MultiheadAttention. Requirements: - Input tensor shape: (batch_size, se...
Optimize Surge Notifications for Rideshare Drivers
Scenario A rideshare marketplace experiences airport demand spikes. When demand exceeds supply, the system can send surge-pricing push notifications t...
Design a Ride-Hailing ETA System
You are a Data Scientist at a ride-hailing company. Design an ETA system used in the rider and driver apps to estimate both pickup ETA and trip ETA. D...