Machine Learning Engineer

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Description

• Optimize, automate, and validate quantitative models using machine learning, statistics, optimization, and simulation techniques. • Develop, schedule, monitor, and maintain robust model training and prediction workflows to ensure optimal performance. • Collaborate with the broader engineering team to implement infrastructure changes that support one or more sports within our platform. • Deploy REST APIs on top of fitted models, utilizing distributed computation to enable real-time integration with client-facing applications. • Work closely with data scientists to define and manage the productionalization of models and the release of platform updates. • Develop and maintain abstractions for model deployment, ensuring workflows run efficiently and are easily adaptable to future use cases. • Assess, provision, monitor, and maintain the appropriate infrastructure and tooling to execute model training and prediction workflows. • Create visualizations using dashboards or application development frameworks to deliver data insights to our clients. • Collaborate and communicate effectively in a distributed work environment, contributing to a dynamic and innovative team. • Engage in rotating platform support duties, ensuring the reliability and performance of our machine learning systems.

Requirements

• Demonstrated experience in software design and development, with a strong foundation in machine learning, statistics, optimization, and simulation. • Hands-on experience developing and deploying machine learning models in cloud-based environments, with distributed computing expertise. • Fluency in Python (preferred), with experience in R or other statistical programming languages. • Familiarity with front-end development languages such as Javascript or Typescript, along with UI frameworks like React or Vue, is a plus. • Proficiency in working with relational databases and SQL, optimizing data management in large-scale systems. • Experience working with Linux servers in virtualized or distributed environments, ensuring stable and secure operations. • Strong problem-solving skills, with the ability to adapt to evolving technical landscapes and workflows.

Benefits

• Comprehensive benefits plan, including medical, dental, vision, disability, life insurance, paid time off, and a retirement/pension contribution plan. • Financial security through competitive compensation and incentives. • Additional educational opportunities via Range can be used for courses, conferences, and other options. • Company equity. • 100% remote-optional work setting.