Explain Model Compression Techniques
Company: Waymo
Role: Machine Learning Engineer
Category: Machine Learning
Difficulty: medium
Interview Round: Technical Screen
Explain quantization-aware training, knowledge distillation, evaluation mode in deep learning frameworks, and contrastive learning. For each topic, describe the purpose, how it works, when it is useful, common pitfalls, and how you would evaluate whether it improved a production model.
Quick Answer: This question evaluates understanding of model compression and representation-learning concepts—quantization-aware training, knowledge distillation, evaluation mode in deep learning frameworks, and contrastive learning—assessing competency in model optimization, resource-aware deployment, and representation quality.