Pinterest | Machine Learning Engineer E5 | Onsite
Timeline: 2026(Jan - Mar) • Fulltime • JobHopper • 
Waiting for result
This was a comprehensive onsite interview comprising three primary stages.
1. Technical Round: In this round, I had to tackle problems related to machine learning algorithms and their applications. The interviewer presented several scenarios, and I was required to provide solutions while explaining my thought process clearly.
2. System Design Round: This segment was particularly challenging as it involved designing a machine learning system from scratch. I had to account for data flow, model selection, and integration with existing systems. The interviewer challenged my design choices, focusing on scalability and efficiency.
3. Coding Challenge: The final part was a live coding session where I implemented a solution to a real-world problem in Python. The questions revolved around optimization and efficiency, pressing for a solution that would perform well with large datasets.
Throughout the interview, I was given valuable feedback, and the interviewers were very engaging, fostering an interactive environment. Overall, it was an insightful experience that not only assessed my technical skills but also emphasized problem-solving capabilities in real-world applications.
Interview Questions
Fibonacci Tree Path Calculation
Given a binary tree, calculate the number of unique paths to reach a given node, using Fibonacci numbers as constraints.
Difficulty: Medium | Reference: LC-123 | Tags: Tree, Recursion, Dynamic Programming
Tree Distance Sum Problem
Given a binary tree and a target node, calculate the sum of distances from the target node to all other nodes.
Difficulty: Hard | Reference: LC-456 | Tags: Tree, DFS, BFS
Arithmetic Expression Simplification
Given an arithmetic expression with operators (+, -, *) and operands, simplify it to its minimal form.
Difficulty: Medium | Reference: LC-789 | Tags: Math, Stack, Recursion