Machine Learning Engineer - St. Louis Cardinals

Summary of Responsibilities

The role of the Machine Learning Engineer is to deploy, maintain, and monitor fault-tolerant systems to preprocess data and apply analytical models for the St. Louis Cardinals. This person will collaborate with data engineers, data scientists, and application developers to create and maintain end-to-end analytic pipelines that feed applications used by front office members, scouts, coaches, trainers, and players.

Essential Functions of the Job

• Gather, clean, and preprocess data to assess its suitability for training models.
• Monitor data quality and model performance, adapting to new data or changing conditions.
• Implement models in production environments with design patterns that scale appropriately with user requests.
• Ensure that models and systems are optimized for performance and cost.
• Work closely with data engineers, data scientists, and application developers to create end-to-end analytical pipelines.

Education and Experience Required

• BS or MS in computer science, data science, mathematics, engineering, or a related field.
• Proficiency in R and/or Python for data science.
• Proficiency in SQL and Git.
• Comfort with Python or Golang for data processing and data engineering
• Ability to communicate and explain software engineering design patterns while collaborating with data scientists, data engineers, and application developers.

Education and Experience Preferred

• Experience interacting with cloud services such as AWS, Microsoft Azure, or Google Cloud.
• Familiarity with docker, kubernetes, and serverless architectures.
• Familiarity with event driven architectures.
• Familiarity with baseball-related data and analytics.