Experience Details
I recently interviewed for a Senior AI Engineer role at a fast-growing tech startup. The 60-minute video call was with the Head of ML and the Lead Data Engineer. We began with a concise walkthrough of my experience—projects in deep learning, model deployment, and MLOps—and then dove into a technical deep-dive and scenario exercises. We wrapped up with discussions about team collaboration, scaling challenges, and roadmap planning.
Interview Questions
Design an end-to-end system for real-time object detection on edge devices. Which architecture would you choose—YOLOv5, MobileNet SSD, or a transformer-based model—and why?
Explain how you’d diagnose and mitigate gradient vanishing/explosion in training a very deep network.
Compare strategies for scaling training across multiple GPUs or nodes (e.g., PyTorch DDP vs. Horovod). What pitfalls have you encountered?
This experience was shared anonymously to help others prepare for their interviews.