Machine Learning Engineer, Data & Systems
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The role
Develop foundation-scale data sets and training recipes to enable scalable model training.
Create methods and recipes for labeling data at foundation-scale, including human and machine labeling workflows.
Build continuous data intake, selection, and incremental updates for large models with automated data collection and flywheels.
Develop evaluation methodologies to assess real-world performance and detect regressions in model updates.
Create and maintain ground-truth-free performance metrics for monitoring system behavior in production.
Collaborate across teams to integrate data and models into onboard and offboard hardware, and contribute to reproducible ML practices.
Create methods and recipes for labeling data at foundation-scale, including human and machine labeling workflows.
Build continuous data intake, selection, and incremental updates for large models with automated data collection and flywheels.
Develop evaluation methodologies to assess real-world performance and detect regressions in model updates.
Create and maintain ground-truth-free performance metrics for monitoring system behavior in production.
Collaborate across teams to integrate data and models into onboard and offboard hardware, and contribute to reproducible ML practices.
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