We seek a Machine Learning Engineer with a passion for baseball and technology to implement, automate, and optimize our data scientists’ quantitative models. Your work will deliver the models that inform the decisions that build a sustainable winning team in Miami.
Key Responsibilities
- Optimize, automate, and validate quantitative models built using statistics, machine learning, optimization, and simulation.
- Develop, schedule, monitor, and maintain model training and prediction workflows.
- Develop and maintain abstractions for model deployment that allow our workflows to run efficiently and be easily adapted to future use cases.
- Assess, provision, monitor, and maintain the appropriate infrastructure and tooling to execute model training and prediction workflows.
- Create visualizations with dashboard or application development frameworks to deliver data insights to Baseball Ops users.
- Deploy REST APIs on top of fitted models using distributed computation to support real-time, client-facing integration.
- Coordinate with the broader engineering team to plan and implement changes to core infrastructure.
- Collaborate with data scientists to define and manage model productionalization and platform release plans.
- Fulfill other related duties and responsibilities, including rotating platform support.
Qualifications
- Academic and/or industry experience in software design and development.
- Academic, industry, and/or research experience with applied mathematical and predictive modeling (statistics, machine learning, optimization, and/or simulation).
- Experience with cloud infrastructure and distributed computing.
- Experience with back-end development, including fluency with Python (preferred), R, or other data-oriented and statistical programming languages.
- Experience with relational databases and SQL development.
- Familiarity working with Linux servers in a virtualized/distributed environment.
- Strong software-engineering and problem-solving skills.
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, age, disability, gender identity, marital or veteran status, or any other protected class.
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