Uber
Ride-hailing and delivery platform with massive real-time data challenges.
4 Rounds
~21 Days
Hard
The Interview Loop
Recruiter Screen (30 min)
Standard fit check, behavioral questions, and resume overview.
Technical Loop (3-4 Rounds)
Deep dive into domain knowledge, coding, and system design.
Interview Question Bank
Machine Learning Engineer
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Technical
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medium
For predicting the exact location (latitude/longitude) of a rider's pickup spot based on historical pin drops, what loss function would you use and why? How would you handle outliers?
#Loss Functions
#Geospatial
#Regression
#Robust Statistics
Machine Learning Engineer
•
Technical
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easy
Uber heavily uses XGBoost for tabular data but Deep Learning for ETA and NLP. Explain the theoretical differences between Gradient Boosted Trees and Neural Networks. When would you strictly prefer one over the other?
#XGBoost
#Deep Learning
#Model Selection
#Bias-Variance Tradeoff
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Senior EngineerFocuses on core competencies, system constraints, and clear communication.
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