Fine-Tuning Feature Store

Fine-Tuning Feature Store is a ml service that serves consistent features to training and inference for adaptation of a model to a domain. It uses versioned feature definitions, freshness checks, and access policies so teams can avoid training-serving skew while keeping evidence, reliability, and public-safe operational boundaries clear.

“The machine learning team used Fine-Tuning Feature Store when the fine-tuning run used curated examples, so the team could avoid training-serving skew before the model moved into evaluation.”