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MLOps

Feature Store

A system providing point-in-time correct training-set generation and a low-latency online store serving identical values.

Why interviewers ask about it

Adopt when multiple teams share features or you need point-in-time joins across many entities - not on day one. A shared transform library plus Redis covers most small teams.

Related terms

Training/Serving Skew

Any difference between how a feature is computed at training time and at inference time.

Point-in-Time Correctness

Building each training row from only the feature values that existed at that row's timestamp.

This term is part of the free AI/ML Engineer interview preparation module - browse the full glossary for every definition.