Meta IC5 Interview Experiences
Summary
Successfully navigated through Meta's IC5 interview process, covering coding challenges, system design, and behavioral rounds. Demonstrated strong problem-solving skills and technical knowledge, with positive feedback from the interviewer.
Full Experience
Round 1: Coding started with a Meeting Scheduler problem involving two-way pointers and arrays. Initially, I struggled to understand the problem but eventually sorted the input and considered boundary conditions, using merge sort and quick sort. The second question was Find the Duplicate Number, which I solved using the fast pointer method similar to linked-list cycle detection. I explained the approach and provided the optimal solution within 10 minutes.
Round 2: System Design focused on designing a Movie Review Aggregator. Since it related to my current work, I outlined the business and ML objectives, discussed feature engineering, and proposed a high-level design. The interviewer emphasized machine learning aspects, and I elaborated on model selection, loss functions, and evaluation metrics.
Round 3: Coding included Next Permutation and Binary Tree Vertical Order Traversal. For the first, I traversed backward to find the first node smaller than subsequent nodes, then swapped and reversed the subarray. For the second, I used BFS with a hash map to track column positions.
Round 4: Behavioral questions covered managing priorities, resolving conflicts, and receiving feedback. I used the STAR method, focusing on team building and leadership. The interviewer was satisfied but asked about my preferred machine learning area.
Interview Questions (4)
This question involves two-way pointers and uses two arrays, with many boundary conditions. At first, I didn't understand it clearly. It is actually similar to a linked list problem. First, I sorted to cover all cases, then drew a diagram while considering the boundary conditions, which was more comprehensive. I mainly used merge sort and quick sort. When the interviewer asked for test cases, I identified several overlooked boundary conditions and made corrections.
I used the fast pointer method, similar to the linked-list cycle detection method. It is essentially a generic algorithm for checking linked-list cycles and is not particularly complex. I explained the solution approach and provided the optimal solution within 10 minutes. I recorded the time and space complexity, but due to time constraints, I only ran a few test cases verbally.
My approach here was to traverse backward from the end, finding the first node smaller than subsequent nodes. I then traversed from the tail, found the node larger than the one found, and swapped it with the smallest value in the subarray. Finally, I reversed the subarray to obtain the answer. Note that the subsequent subarray is monotonically decreasing.
I used BFS. I used a hash map to store the node values at all column positions and recorded the maximum and minimum column values.
Preparation Tips
Prepared for the interview by focusing on problem-solving techniques, including sorting algorithms and data structure concepts. For the system design round, I reviewed machine learning objectives and design patterns related to my current work. For behavioral rounds, I practiced STAR method examples related to team building and leadership.