Explain LLM training, RL, and evaluation

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Quick Overview

This question evaluates understanding of the full large language model lifecycle and associated competencies, including pre-training, supervised fine-tuning, preference optimization, reinforcement learning–based post-training, reward design, optimization stability, common failure modes, and evaluation metrics.

Explain LLM training, RL, and evaluation

Company: Cohere

Role: Machine Learning Engineer

Category: Machine Learning

Difficulty: medium

Interview Round: Onsite

Overview: This question evaluates understanding of the full large language model lifecycle and associated competencies, including pre-training, supervised fine-tuning, preference optimization, reinforcement learning–based post-training, reward design, optimization stability, common failure modes, and evaluation metrics.

Read the full Cohere Machine Learning Engineer interview experience this question came from

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Cohere
Dec 25, 2025
mediumMachine Learning EngineerOnsiteMachine Learning
9
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