
Rokt Machine Learning Engineer Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 11 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Rokt.
Machine Learning Engineer
Rokt was super responsive and easy to schedule with, always getting back to me fast with feedback. I really liked the people I met, both online and in person. The process was quick, usually getting results the next day and setting up the next interview. A cool thing was after a few rounds, HR sat down with me to go over the feedback from each person I talked to. That openness was awesome, and the feedback was always fair and helpful. Even though I ended up taking another job for my career path, Rokt's HR team really tried hard to get me to join, which made me feel respected and valued. I felt totally supported by them.
- Regarding Rokt's transparent compensation policy, what are your thoughts?
AI Software Developer
I went through some aptitude tests, then a HireVue interview, and finally a take-home assessment that I had 72 hours to complete. The problem was pretty straightforward but had a tricky part. The downside of this AI-driven hiring approach is that I didn't interact with anyone during the whole process. I even questioned if it was a scam. The hiring process could have been better, as I didn't receive any feedback.
- What are your reasons for wanting to join Rokt?
Machine Learning Engineer
The process started with a personality quiz, which I refused to do. Then, a third-party recruiter contacted me, and I spoke with an Engineering Manager, the only positive interaction. I had a choice between a take-home LeetCode or an in-person LeetCode; I chose the latter. These were challenging, especially for Sydney's tech scene. I completed them successfully. Next, I had an in-person coding interview with the Engineering Manager, which was straightforward, and we discussed my past work's impact. The ML interviewer seemed to have only taken an online course and went through a checklist without much depth. The Systems Design round was difficult due to my lack of web-scale experience; I struggled with designing a system when told I couldn't access certain data and was criticized for my lack of knowledge. Despite failing Systems Design, I was downleveled for the CTO interview. During this interview, it became clear the company is primarily sales-driven with basic ML. The CTO described a 'scrappy startup culture' unsuitable for their size. They did not send a rejection email; my recruiter had to follow up.
- How would you design Rokt's product recommendation system, similar to Amazon's?
- Tell me about the impact you've had in your previous role.
- Walk me through your understanding of Machine Learning.
Rokt Machine Learning Engineer Interview Questions
Quoted word for word from Rokt interview reports.
“Design a CVR prediction model”
Read reports →“Can you explain the ML pipeline and feature store?”
Read reports →“How would you design and implement a two-tower model for a large-scale recommendation system, specifically focusing on building the user and item towers separately?”
Read reports →“Regarding Rokt's transparent compensation policy, what are your thoughts?”
Read reports →“Can you give me a deep dive into the architecture of two-tower models?”
Read report →“How would you design Rokt's product recommendation system, similar to Amazon's?”
Read report →“What do you know about basic databases?”
Read report →“Can you work with teams in Australia from the US?”
Read report →“Can you design a system, given constraints on data access and potentially using S3?”
Read report →Formats, difficulty and experience
Across all 11 Rokt interview reports.