Cracking the Applied Coding Challenge: Transforming Coordinate Systems for Unmanned Vehicles

applied | | Interview Experience

Interview Date: Not specified
Result: Not specified
Difficulty: Not specified

Interview Process

The interview process consisted of four rounds. The first round involved coding a solution related to transforming the coordinate system of a car, which is relevant to unmanned vehicles. The following rounds included discussions with managers that were insightful and focused on the candidate’s fit within the team. There was a group introduction at the beginning.

Technical Questions

  1. Coordinate Transformation
    Related to unmanned vehicles.

  2. Machine Learning Coding
    Involved debugging a model (ViT) for MNIST classification, focusing on issues related to Transformers, such as mask and padding.

  3. System Design
    Related to unmanned vehicles, discussed in a conventional manner.

Tips & Insights

The interview atmosphere was positive, with nice interviewers and engaging discussions. The candidate felt a strong match with the team regarding future vision and goals. The overall impression was that the team is strong and the company has sufficient funding. Debugging questions were interesting but not overly challenging, as long as the candidate was familiar with single-step debugging in PyTorch.