Machine Learning Engineer II
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The role
Design, build, and optimize data pipelines and ML workflows that support model training, validation, deployment, and monitoring.
Partner with data scientists to productionize models, ensuring scalability, reliability, and reproducibility.
Implement ML automation and orchestration using tools like Databricks and MLflow.
Contribute to architecture discussions and drive improvements in ML platform components, feature pipelines, and experimentation processes.
Write clean, maintainable Python code with a focus on performance in distributed environments (e.g., PySpark).
Strengthen operational excellence by enhancing observability, failure handling, CI/CD integration, and model lifecycle management, and participate in code reviews.
Partner with data scientists to productionize models, ensuring scalability, reliability, and reproducibility.
Implement ML automation and orchestration using tools like Databricks and MLflow.
Contribute to architecture discussions and drive improvements in ML platform components, feature pipelines, and experimentation processes.
Write clean, maintainable Python code with a focus on performance in distributed environments (e.g., PySpark).
Strengthen operational excellence by enhancing observability, failure handling, CI/CD integration, and model lifecycle management, and participate in code reviews.
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