
Observe.AI Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 40 interview experiences · FREE TO READ
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17 roles · 40 reportsCandidate interview experiences
First-hand accounts from people who interviewed at Observe.AI.
Technical Support Engineer Intern
My interview process involved three rounds: first, a phone call, then a technical round, and finally an HR round where I visited the office. All three rounds were manageable and not overly challenging. However, I felt my time was wasted as I'm a full-time employee looking to transition into a TSE role, but applied for this internship. I want to emphasize to this company and others: if you're hiring students or unemployed individuals for internships, please don't interview experienced, full-time employees after reviewing their resumes. You already know you won't hire a full-time person for an intern position. So why make us go through all three rounds just to reject us in the end? Please respect candidates' time.
- Write an SQL query.
- Draft an email.
- Assess your communication skills.
Product Manager
It all started with HR reaching out. The whole experience was smooth and organized. She gave me the lowdown on the job and walked me through the interview stages. For each step, she'd call first to give me the scoop on who I'd be talking to and what the round would be like, then follow up with an email. So I always knew what was coming. There were five rounds total, including an intro, a case study, and a chat with the Engineering Manager. Funnily enough, one person ended up handling 4 of the 5 rounds, which was awesome. She was super respectful and the discussions were so engaging and thought-provoking that I felt like I learned a ton after each one. Didn't get the job in the end, but that's no reason to complain about them or the company.
- Can you describe how a company known for poor customer service could improve its reputation?
Machine Learning Engineer
So there were a few rounds. First was a chat with the Hiring Manager, then a technical round on basics, followed by another technical round focusing on my projects and experience. After that, there was a hands-on technical round. Then, another discussion with the hiring manager and finally a chat with HR. Everything was over video calls and it took about 3 weeks. The TA team was super quick to respond to anything I asked. They also let me know what each upcoming discussion would cover, which was great for prepping. I really liked the hands-on part, the interviewer helped me figure out the problem and we talked through it to get to a solution. The questions were pretty unique and made me think. Overall, it was a good experience. They seemed to care a lot about how much knowledge we had and how deep it went.
- Could you explain the trade-off between Bias and Variance?
- What can you tell me about CNNs?
- How does SVM work, perhaps with a slight variation?
DevOps Engineer
The interview process consisted of a total of 7 rounds. There were 2 coding rounds - 1st and the 4th, 2 technical discussions - 2nd and the 3rd, 2 Hiring managers, and 1 culture check round. The first round was a hacker rank-based coding round with 3 python and 1 Kubernetes problem. It was a bit tough. The next two rounds were purely technical discussions and were average, The fourth round was again a coding round which was done on a screen share with one of the developers. In this round, he will give you a problem and will try to see how good you are at DSA. The next two rounds were a mix of technical and culture check. The last round which was the HR round was purely culture check and to get feedback of all the rounds. The whole interview process took less than 2 weeks. But after completing all the 7 rounds of interview, I was kind of ghosted by the HR. She made up excuses for more than 2 weeks and then finally told me I did not clear the interview. When I asked for a reason, she told me that I did not perform well at DSA.
- Technical discussions were based on AWS cloud
- Docker questions
- Kubernetes questions
Observe.AI Interview Questions
Quoted word for word from Observe.AI interview reports.
“Given n problem ideas and m tags, with problems having associated tags (2d array `tags` where `tags[i][j] = 1` if problem `i` has tag `j`) and preparation costs (array `cost` of length `n`), and knowing that each tag is covered by at least one problem, find the minimum cost to select problems that cover all `m` tags.”
Read reports →“How can speech processing be used to distinguish between the voice of an average person and that of an elderly person?”
Read reports →“Write an SQL query.”
Read reports →“Can you explain the gates within an LSTM model?”
Read reports →“what are some simple python sorting problems”
Read report →“Who cares about the questions when they don't follow up?”
Read report →“Data Structures and Algorithms: How would you implement a rate limiter?”
Read report →“And what about Random Forests?”
Read report →“How does SVM work, perhaps with a slight variation?”
Read report →Formats, difficulty and experience
Across all 40 Observe.AI interview reports.