Staff Machine Learning Engineer, ML Platform
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El puesto
Design and own a scalable ML Platform for large-scale models.
Define end-to-end MLOps patterns covering data preparation, model management, experiment tracking, and deployment.
Lead zero-to-one development and support of a graph ML codebase that abstracts common patterns for scalability.
Collaborate with ML engineers to optimize performance, training time, and GPU cost in a distributed environment.
Improve batch data processing in data warehouses using Apache Beam, Spark, and Ray Data.
Architect pipelines to build and maintain massive graph structures with billions of nodes and edges.
Define end-to-end MLOps patterns covering data preparation, model management, experiment tracking, and deployment.
Lead zero-to-one development and support of a graph ML codebase that abstracts common patterns for scalability.
Collaborate with ML engineers to optimize performance, training time, and GPU cost in a distributed environment.
Improve batch data processing in data warehouses using Apache Beam, Spark, and Ray Data.
Architect pipelines to build and maintain massive graph structures with billions of nodes and edges.
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