Job Description
Own pipelines and DAGs that move data, features, embeddings, and models through the ML lifecycle.
Design/maintain ranking and retrieval services that run models in real-time.
Build scalable model-serving APIs, ensuring reliability, efficiency, and performance.
Create reusable infrastructure that other MLEs depend on to train, deploy, and iterate on models.
Enable modeling with better systems, features, and deployment pathways.
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