技能档案

LLM Evaluation

Benchmarks, BLEU/ROUGE metrics, human eval, LLM-as-judge, generation quality assessment

Machine Learning & AI LLM & Generative AI

角色数

包含此技能的角色

级别数

结构化成长路径

必要要求

其余 2 个可选

Machine Learning & AI

LLM & Generative AI

2026/3/17

选择当前级别并对比期望。下方卡片显示晋升所需掌握的内容。

各级别期望

表格展示从初级到首席的技能深度变化。点击行查看详情。

角色	必要性	描述
AI Product Engineer		Understands the fundamentals of LLM Evaluation. Applies basic practices in daily work. Follows recommendations from the team and documentation.
LLM Engineer	必要	Knows basic LLM evaluation metrics: perplexity, BLEU, ROUGE. Runs standard benchmarks (MMLU, HellaSwag) under mentor guidance and interprets basic results.

角色	必要性	描述
AI Product Engineer		Independently applies LLM Evaluation in practice. Understands trade-offs of different approaches. Solves typical tasks independently.
LLM Engineer	必要	Independently designs evaluation pipelines: custom benchmarks, domain-specific eval sets, human evaluation protocols. Compares models across multiple metrics for production decision-making.

角色	必要性	描述
AI Product Engineer	必要	Has deep expertise in LLM Evaluation. Designs solutions for production systems. Optimizes and scales. Mentors the team.
LLM Engineer	必要	Designs comprehensive evaluation frameworks: automated eval with LLM-as-judge, contamination detection, statistical significance testing. Develops domain-specific benchmarks for production tasks.

角色	必要性	描述
AI Product Engineer	必要	Defines LLM Evaluation strategy at the team/product level. Establishes standards and best practices. Conducts reviews.
LLM Engineer	必要	Defines evaluation standards for the LLM team. Establishes model evaluation guidelines, regression testing, benchmark management. Coordinates human evaluation processes and quality assurance.

角色	必要性	描述
AI Product Engineer	必要	Defines LLM Evaluation strategy at the organizational level. Establishes enterprise approaches. Mentors leads and architects.
LLM Engineer	必要	Shapes enterprise evaluation strategy. Defines approaches to continuous evaluation, model quality governance, and benchmark development. Ensures alignment between evaluation metrics and business objectives.

Junior 2 要求

AI Product Engineer

Understands the fundamentals of LLM Evaluation. Applies basic practices in daily work. Follows recommendations from the team and documentation.
LLM Engineer
必要

Knows basic LLM evaluation metrics: perplexity, BLEU, ROUGE. Runs standard benchmarks (MMLU, HellaSwag) under mentor guidance and interprets basic results.

Middle 2 要求

AI Product Engineer

Independently applies LLM Evaluation in practice. Understands trade-offs of different approaches. Solves typical tasks independently.
LLM Engineer
必要

Independently designs evaluation pipelines: custom benchmarks, domain-specific eval sets, human evaluation protocols. Compares models across multiple metrics for production decision-making.

Senior 2 要求

AI Product Engineer
必要

Has deep expertise in LLM Evaluation. Designs solutions for production systems. Optimizes and scales. Mentors the team.
LLM Engineer
必要

Designs comprehensive evaluation frameworks: automated eval with LLM-as-judge, contamination detection, statistical significance testing. Develops domain-specific benchmarks for production tasks.

Lead / Staff 2 要求

AI Product Engineer
必要

Defines LLM Evaluation strategy at the team/product level. Establishes standards and best practices. Conducts reviews.
LLM Engineer
必要

Defines evaluation standards for the LLM team. Establishes model evaluation guidelines, regression testing, benchmark management. Coordinates human evaluation processes and quality assurance.

Principal 2 要求

AI Product Engineer
必要

Defines LLM Evaluation strategy at the organizational level. Establishes enterprise approaches. Mentors leads and architects.
LLM Engineer
必要

Shapes enterprise evaluation strategy. Defines approaches to continuous evaluation, model quality governance, and benchmark development. Ensures alignment between evaluation metrics and business objectives.

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