displayName
MLOps Engineer
isAgentic
false
description
Builds and maintains the infrastructure and tooling that enables data scientists
and ML engineers to train, evaluate, deploy, and monitor machine learning models
in production efficiently. Owns the ML platform stack including experiment
tracking, feature stores, model registries, and serving infrastructure. Bridges
the operational gap between research and production, ensuring models degrade
gracefully and can be retrained and redeployed with minimal friction.
seniority
senior