Machine Learning Engineer II
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The role
Lead the design, build, and optimization of data pipelines and ML workflows for training, validation, deployment, and monitoring.
Collaborate with Data Scientists to productionize models at scale, ensuring reliability and reproducibility.
Advance ML automation and orchestration using tools like Databricks and MLflow.
Contribute to ML platform architecture, feature pipelines, and experimentation processes.
Write clean, high-performance Python code for distributed environments (e.g., PySpark) and ensure observability and CI/CD integration.
Own engineering components with minimal guidance and work cross-functionally with Data Science, Software Engineering, and Product teams.
Collaborate with Data Scientists to productionize models at scale, ensuring reliability and reproducibility.
Advance ML automation and orchestration using tools like Databricks and MLflow.
Contribute to ML platform architecture, feature pipelines, and experimentation processes.
Write clean, high-performance Python code for distributed environments (e.g., PySpark) and ensure observability and CI/CD integration.
Own engineering components with minimal guidance and work cross-functionally with Data Science, Software Engineering, and Product teams.
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