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Description: HouseSigma’s the most used real estate platform in Canada. We are able to collect huge amounts of user activities data. The objective is to build a recommendation engine that is able to recommend relevant real estate listings to users in real time based on the user's past activities. Goal: You are provided sample user activity data in json format. Note that due to the volume of user activity data, it’s stored in Mongodb in Json format. Please use machine learning techniques to build a recommendation engine that recommends relevant listing content to users.
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ML Engineer

Interviewed at HouseSigma

4.6★
Aug 15, 2023

Description: HouseSigma’s the most used real estate platform in Canada. We are able to collect huge amounts of user activities data. The objective is to build a recommendation engine that is able to recommend relevant real estate listings to users in real time based on the user's past activities. Goal: You are provided sample user activity data in json format. Note that due to the volume of user activity data, it’s stored in Mongodb in Json format. Please use machine learning techniques to build a recommendation engine that recommends relevant listing content to users.

For the most part they were basic probability and coding. After reading other reviews, I seem to think they're recycling the interview problems: - Basic high-school probability and number puzzles. - The CTO wanted to implement a linked list, and reverse it (extra credit for in place reversal in a single pass). - One of the engineers tried to prove he was smarter than you but providing very sparse details on his problems. It was also a bit annoying when he didn't acknowledge any correct answers and simply wanted to move on to the next problem.
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ML Engineer

Interviewed at SoundHound

3.5★
Jun 21, 2022

For the most part they were basic probability and coding. After reading other reviews, I seem to think they're recycling the interview problems: - Basic high-school probability and number puzzles. - The CTO wanted to implement a linked list, and reverse it (extra credit for in place reversal in a single pass). - One of the engineers tried to prove he was smarter than you but providing very sparse details on his problems. It was also a bit annoying when he didn't acknowledge any correct answers and simply wanted to move on to the next problem.

How would you detect these spots in a Petri dish? Please, describe how circle detection works. Tell me about Hough transform. Describe this piece of code in Python, what does it do? How would you describe this weird behavior? What do you know about multi-processing in Python?
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ML/AI Engineer

Interviewed at MSD

4★
Nov 15, 2023

How would you detect these spots in a Petri dish? Please, describe how circle detection works. Tell me about Hough transform. Describe this piece of code in Python, what does it do? How would you describe this weird behavior? What do you know about multi-processing in Python?

There were 4 rounds . 2 of online assessment , 1 Technical and 1 HR . in technical interview they asked about the projects , their description and some pretty basic questions of numpy , ML , python . The HR round was quite interactive .

AI/ML Engineer

Interviewed at Capsitech IT Services

2.2★
Sep 26, 2025

There were 4 rounds . 2 of online assessment , 1 Technical and 1 HR . in technical interview they asked about the projects , their description and some pretty basic questions of numpy , ML , python . The HR round was quite interactive .

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