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causaLens Machine Learning Engineer Interview Questions
& Process

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

Based on 10 interview experiences · FREE TO READ

3 Rounds average
Average Typical difficulty
40% Positive experience

Candidate interview experiences

First-hand accounts from people who interviewed at causaLens.

Showing 3 of 10
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Machine Learning Engineer

Engineering · a year ago

Mid Average Neutral experience No offer 5 rounds
Interview process
Recruiter call Technical screen Technical screen Technical screen Panel
Interview formats
Coding Technical Behavioral

The hiring process had three main steps. First, an interview with HR. Second, an interview with the Team Lead. Third, what they called 'Day 0'. Day 0 was pretty intense, with a 3-hour technical assessment that focused mainly on coding but also touched on machine learning. After that, there were three 30-minute tech interviews and a final 30-minute cultural interview. The interviews were mostly chill, except for one where they really went deep into the math behind machine learning concepts.

Confirmed questions3 questions
  • Can you explain how the Linear Regression algorithm learns?
  • What are the concepts of time series data and how do you handle filling NA values?
  • In your opinion, what is the most crucial element in managing a team?
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causaLens

Machine Learning Engineer

Engineering

Mid Average Negative experience No offer 4 rounds
Interview process
Recruiter call Technical screen Technical screen Onsite
Interview formats
Behavioral Technical

It was a pretty disorganized hiring process. The HR manager didn't really give me any info on what was coming next. First, I had to fill out a questionnaire with typical questions like why I'm applying, why I want to work at causaLens, and why I'm interested in this specific role. Then, there was a 30-minute interview with someone currently in the role. It was mostly easy technical questions and not much about my background. By the time I could ask questions, the interview was almost over because the interviewer had another meeting right after. After that, I had a 20-minute interview with the hiring manager, which ended up lasting about 50 minutes. Surprisingly, it was also mostly technical questions, which I didn't expect given the short scheduled time. The last stage was 'Day Zero,' where I spent the whole day doing various tasks and had several interviews. Everyone except the CEO, who was quite arrogant and condescending, was really friendly and seemed like great people to work with. A major letdown was seeing their website talk about diversity and inclusion, but all the technical folks I interviewed with and saw on LinkedIn were very similar, lacking diversity. It would be better to acknowledge this issue and work on it rather than pretend it's not a problem at causaLens.

Confirmed questions5 questions
  • Tell me about why you're applying.
  • What makes you interested in causaLens?
  • Why this particular position?
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causaLens

Machine Learning Engineer

Engineering

Mid Difficult Positive experience Accept offer 5 rounds
Interview process
Recruiter call Technical screen Onsite
Interview formats
Behavioral Technical Coding

So first I had a quick call to chat about my background and why I wanted to join this company. After that, there was a longer technical interview. This technical interview had a coding part and also a discussion about machine learning stuff. The last part was called Day 0. It was in the office and had a 2 hour coding test, then three 30 minute interviews, and one of those was about the coding test I did.

Confirmed questions2 questions
  • What do you understand by casual AI?
  • What loss function would you use when performing logistic regression?

causaLens Machine Learning Engineer Interview Questions

Quoted word for word from causaLens interview reports.

Solve a coding problem about calculating a moving window sum without a specified window size.

Read reports

What loss function would you use when performing logistic regression?

Read reports

Can you explain how the Linear Regression algorithm learns?

Read report

Can you explain what regularization is in machine learning?

Read report

What are the concepts of time series data and how do you handle filling NA values?

Read report

Formats, difficulty and experience

Across all 10 causaLens interview reports.

Interview formats

Technical 36%
Behavioral 32%
Coding 28%
System Design 4%

Interview difficulty

Easy 10%
Average 50%
Difficult 40%

Candidate experience

Neutral 20%
Positive 40%
Negative 40%