Mine Novel Images from Unlabeled Data
Company: OpenAI
Role: Machine Learning Engineer
Category: ML System Design
Difficulty: medium
Interview Round: Technical Screen
Design a machine learning system that mines novel or interesting images from a massive unlabeled image corpus. The corpus is too large for exhaustive human review. You may use human labelers, but the system should not depend heavily on manual labeling.
Your design should cover:
1. How to define and measure novelty or interestingness.
2. Data ingestion, deduplication, filtering, and storage.
3. Model choices for image representation and scoring.
4. How to use limited human labels effectively.
5. How to rank, diversify, and sample candidate images.
6. Evaluation metrics and online monitoring.
7. Scaling considerations for a very large corpus.
Quick Answer: This question evaluates skills in machine learning system design, unsupervised novelty detection, representation learning, scalable data ingestion and storage, human-in-the-loop labeling, ranking and sampling strategies, and monitoring within the ML System Design domain.