Machine Learning Data Engineer, Replica Pipelines
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El puesto
Own data ingestion and build reliable pipelines to normalize and validate customer and synthetic data for Replica and ML model development.
Define data standards by creating schemas, validation checks, and quality metrics to ensure clean, consistent datasets.
Develop curation tooling for dataset filtering, versioning, and annotation support to enable efficient data governance.
Enable ML workflows by generating high-quality data feeds for training and evaluation across models.
Collaborate closely with ML engineers to translate data needs into scalable, production-ready data infrastructure.
Leverage Python, cloud storage, and 3D/vision fundamentals to manage large-scale datasets used in autonomous systems.
Define data standards by creating schemas, validation checks, and quality metrics to ensure clean, consistent datasets.
Develop curation tooling for dataset filtering, versioning, and annotation support to enable efficient data governance.
Enable ML workflows by generating high-quality data feeds for training and evaluation across models.
Collaborate closely with ML engineers to translate data needs into scalable, production-ready data infrastructure.
Leverage Python, cloud storage, and 3D/vision fundamentals to manage large-scale datasets used in autonomous systems.
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