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 January 25, the median salary range for US Retrieval-augmented generation jobs was $145K to $205K per year. In this month we've identified salaries as high as $650K, and as low as $40K.
Salary Trend
$145K-205K
Median Salary
$323K-650K
High Salary
$40K-85K
Low Salary
