Lead MLOps Engineer
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El puesto
Lead a Databricks-based MLOps program focused on scalable, production-grade AI/ML fraud detection models.
Oversee Databricks clusters and Spark-based data pipelines, ensuring robust data processing and reliability.
Drive MLOps practices including model monitoring, feature catalog, experiment tracking, and CI/CD to govern the model lifecycle from development to production.
Own and maintain MLOps solutions, leveraging open-source tooling or third-party vendors, and develop executive dashboards reflecting build, deploy, and run metrics.
Provide technical leadership to a team of MLOps engineers, collaborating with data scientists and software engineers while upholding data governance and security standards.
Require strong coding in Python (and optionally Java/C++), SQL proficiency, cloud experience, data observability, data ingestion/integration, and DevOps/SRE practices.
Oversee Databricks clusters and Spark-based data pipelines, ensuring robust data processing and reliability.
Drive MLOps practices including model monitoring, feature catalog, experiment tracking, and CI/CD to govern the model lifecycle from development to production.
Own and maintain MLOps solutions, leveraging open-source tooling or third-party vendors, and develop executive dashboards reflecting build, deploy, and run metrics.
Provide technical leadership to a team of MLOps engineers, collaborating with data scientists and software engineers while upholding data governance and security standards.
Require strong coding in Python (and optionally Java/C++), SQL proficiency, cloud experience, data observability, data ingestion/integration, and DevOps/SRE practices.
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