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System Design
a year ago
Build a service for log management across distributed systems.
Machine Learning Engineer

Grab

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a year ago
Metrics and Experimentation
a year ago
If you were tasked with building a metric to compare two user's Netflix recommended lists of movie/tv show preferences, how would you approach this challenge?
Machine Learning Engineer

Grab

Apple

Shopee

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a year ago
ML Knowledge
a year ago
How do you approach cleaning and restructuring data to optimize its use in machine learning?
Machine Learning Engineer

Grab

Roku Logo

Roku

Robinhood Logo

Robinhood

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a year ago
ML Knowledge
a year ago
Can you discuss the properties of DMatrix in XGBoost and compare it with other data structures used in the field of gradient boosting?
Machine Learning EngineerData Scientist

Grab

Viber Logo

Viber

Deloitte Logo

Deloitte

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a year ago
System Design
a year ago
Design a system for real-time processing of satellite imagery.
Machine Learning Engineer

Grab

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a year ago
System Design
a year ago
Design a system for online advertising.
Machine Learning Engineer

Grab

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a year ago
System Design
a year ago
Architect a multi-user document editing service like Google Docs.
Machine Learning Engineer

Grab

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a year ago
System Design
a year ago
Design a personalized content feed like Facebook's.
Machine Learning Engineer

Grab

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a year ago
ML Knowledge
2 years ago
What techniques do you employ to manage categorical data with high cardinality?
Machine Learning Engineer

Grab

Huawei Logo

Huawei

Adobe Logo

Adobe

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2 years ago
ML Knowledge
2 years ago
What is the significance of the area under an ROC curve? Can you compare and contrast bagging and boosting in terms of error reduction?
Machine Learning EngineerData Scientist

Grab

Zillow Logo

Zillow

Wish Logo

Wish

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2 years ago

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Machine Learning Engineer

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System Design
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Machine Learning Engineer

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ML System Design
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Grab

Machine Learning Engineer

Prepare for Behavioral interview at Grab

Behavioral

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*All interview questions are submitted by recent Grab Machine Learning Engineer candidates, labelled and categorized by Prepfully, and then published after being verified by Machine Learning Engineers at Grab.

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