Machine Learning Engineer with PySpark
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The role
Lead the ML engineering effort to productionize, deliver, and integrate ML solutions within the business.
Design and implement architecture for model evaluation and model serving infrastructure.
Identify business areas that could benefit from ML, collaborating with technology and operations leaders to define achievable outcomes.
Work with a team of data scientists, analysts, statisticians, and creative technologists to build scalable ML pipelines.
Implement production ML systems using Python, R, and AWS; develop data processing and deployment pipelines with Airflow, Beam, PySpark, and Spark tooling.
Apply software development best practices, MLOps, SQL/Hive, Linux, and Spark-based tooling to deliver reliable solutions.
Design and implement architecture for model evaluation and model serving infrastructure.
Identify business areas that could benefit from ML, collaborating with technology and operations leaders to define achievable outcomes.
Work with a team of data scientists, analysts, statisticians, and creative technologists to build scalable ML pipelines.
Implement production ML systems using Python, R, and AWS; develop data processing and deployment pipelines with Airflow, Beam, PySpark, and Spark tooling.
Apply software development best practices, MLOps, SQL/Hive, Linux, and Spark-based tooling to deliver reliable solutions.
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