Evaluate Noisy Data for LLM Post-Training
Company: Mercor
Role: Machine Learning Engineer
Category: Machine Learning
Difficulty: medium
Interview Round: Technical Screen
Quick Answer: This question evaluates competency in post-training data curation and experimental judgment for large language models, including assessing noisy dataset suitability, label correctness, distributional fit, safety/privacy risks, and the ability to demonstrate evidence that additional data does not degrade existing capabilities.