Retrieval-augmented generation salary in the US
Retrieval-Augmented Generation (RAG) is a technique in natural language processing (NLP) that enhances the accuracy and relevance of responses generated by large language models (LLMs). RAG works by combining the strengths of both retrieval-based models, which extract information from external sources, and generative models, which create original content.
In December 24, the median salary range for US Retrieval-augmented generation jobs was $140K to $217K per year. In this month we've identified salaries as high as $425K, and as low as $44K.
Salary Trend
$140K-217K
Median Salary
$250K-425K
High Salary
$44K-83K
Low Salary
