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 October 24, the median salary range for US Retrieval-augmented generation jobs was $133K to $210K per year. In this month we've identified salaries as high as $609K, and as low as $53K.
Salary Trend
$133K-210K
Median Salary
$325K-609K
High Salary
$53K-100K
Low Salary
