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MakeSpace Software Engineer Interview Questions
& Process

Real candidates share what happened, how many rounds they had,
and how the experience turned out.

Based on 6 interview experiences · FREE TO READ

2.7 Rounds average
Average Typical difficulty
16.7% Positive experience

Candidate interview experiences

First-hand accounts from people who interviewed at MakeSpace.

Showing 3 of 6
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MakeSpace

Software Engineer

Engineering

Entry Average Negative experience No offer 3 rounds
Interview process
Recruiter call Phone screen Technical screen
Interview formats
Coding Behavioral

I applied on LinkedIn and a recruiter reached out in about a week. We had a call to discuss the company and open roles. Then, I spoke with a hiring manager who went over the job details, what they expect, and their current products. After that, I had a tech screen with Karat IO. It was an hour long, with two coding questions. They were pretty simple, mainly about parsing strings and creating an aggregated output. I managed to complete one and explained my approach for the second before time ran out. I messaged the recruiter two days later for an update, but they never got back to me. Totally ghosted, no info on my application.

Confirmed questions1 question
  • Can you parse a list of parts (strings) and a list of required parts for a product to determine all the products that can be built? This involves matching strings and tracking the parts needed for each product.
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MakeSpace

Senior Software Engineer

Engineering

Senior Average Neutral experience No offer 3 rounds
Interview process
Recruiter call Take home Technical screen
Interview formats
Technical Coding

The interview started with a quick screening call to go over my background and some basic computer science ideas. Then there was this unpaid coding challenge, which felt like a waste of time so I just skipped it.

Confirmed questions2 questions
  • Given a JSON file with geographic points (latitude, longitude, id), create a Python script that accepts an integer 'n'. The script should read the file and output the IDs of the points, divided into 'n' groups, into a file named 'groups.json'. This output file should be a list of lists, containing dictionaries similar to the original points.
  • As a follow-up to the previous task, optimize the grouping of addresses for daily van routes. The goal is to ensure that each van has a comparable number of stops. The optimization should consider both the geographical closeness of the stops, using a function from the first stretch goal, and maintaining balanced group sizes for each van.
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MakeSpace

Software Developer

Engineering

Entry Easy Positive experience No offer 1 round
Interview process
Technical screen
Interview formats
Technical

The interviewer was nice and helpful, giving hints when I got stuck. I didn't get the job but learned a lot.

Confirmed questions1 question
  • Tell me about the data structure you are most familiar with.

MakeSpace Software Engineer Interview Questions

Quoted word for word from MakeSpace interview reports.

Given a JSON file with geographic points (latitude, longitude, id), create a Python script that accepts an integer 'n'. The script should read the file and output the IDs of the points, divided into 'n' groups, into a file named 'groups.json'. This output file should be a list of lists, containing dictionaries similar to the original points.

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Can you parse a list of parts (strings) and a list of required parts for a product to determine all the products that can be built? This involves matching strings and tracking the parts needed for each product.

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Tell me about the data structure you are most familiar with.

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Can you describe a limitation you encountered with the Django framework and your solution to overcome it?

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Can you describe a challenge you faced and how you overcame it?

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Formats, difficulty and experience

Across all 6 MakeSpace interview reports.

Interview formats

Technical 40%
Behavioral 30%
Coding 30%

Interview difficulty

Easy 16.7%
Average 83.3%
Difficult 0%

Candidate experience

Neutral 33.3%
Negative 50%
Positive 16.7%