Surprisingly straightforward — I expected tougher questions for a Machine Learning Engineer role. The first technical round focused on system design, where they asked me to develop a recommendation system for Facebook Reels. Later, I tackled regularization concepts and a DSA question about finding the kth largest element in an array. The interesting part was that I’d just reviewed a similar breakdown on PracHub, which made the discussion feel familiar. Overall, a positive experience, and I was thrilled to accept the offer afterward.
Interview questions [3]
Question 1
Design a recommendation system for Facebook Reels feed
The interview process went well, went through 2 coding rounds, 1 design and 1 behavior, the coding is two easy questions per round. I think the interviewer expect you to have a good understanding of the algo and want you to talk through it, instead of just implementing it.
Interview questions [1]
Question 1
All the questions are common meta style questions, easy and standard
Applied online. Received a recruiter screen within two weeks covering background and role fit. Followed by a technical phone screen with coding (LeetCode medium-hard, arrays/graphs). Then a virtual onsite with 4 rounds: 2 coding, 1 ML system design (recommendation/ranking system), and 1 behavioral. Interviewers were professional and gave time to ask questions. Results communicated within a week post-onsite.