bridgewater | Machine Learning Engineer | Interview Experience
Interview Date: Not specified
Result: Not specified
Difficulty: Not specified
Interview Process
The interview process consisted of three rounds. The first round was with the Head of AI, where the candidate was asked about their background and completed a data manipulation task using either PyTorch or NumPy. The conversation was enjoyable. The second round involved a coding challenge with questions related to breadth-first search (BFS) and depth-first search (DFS). The final round focused on system design, where the candidate was tasked with designing a fully automated parking system.
Technical Questions
- Data manipulation (data manipulation, standardization, linear algebra)
- BFS, DFS, Graph Theory
- System design for an automated parking system (system design, microservices, cloud architecture)
Tips & Insights
The candidate felt underprepared for the system design interview, as their background was primarily in recommendation systems. It may be beneficial to prepare for a broader range of topics, especially in software design, when applying for positions that require diverse skills.