Explain LLM post-training methods and tradeoffs
Company: Scale AI
Role: Machine Learning Engineer
Category: Machine Learning
Difficulty: easy
Interview Round: Onsite
Quick Answer: This question evaluates a practitioner's knowledge of LLM post-training methods—including supervised fine-tuning, preference optimization approaches (RLHF and direct preference losses), safety and alignment interventions, and evaluation beyond loss—within the Machine Learning domain.
