October 26
πΊπΈ United States β Remote
β° Full Time
π‘ Mid-level
π Senior
π€ Machine Learning Engineer
β’ Optimize, automate, and validate quantitative models using machine learning, statistics, optimization, and simulation techniques. β’ Develop, schedule, monitor, and maintain robust model training and prediction workflows to ensure optimal performance. β’ Collaborate with the broader engineering team to implement infrastructure changes that support one or more sports within our platform. β’ Deploy REST APIs on top of fitted models, utilizing distributed computation to enable real-time integration with client-facing applications. β’ Work closely with data scientists to define and manage the productionalization of models and the release of platform updates. β’ Develop and maintain abstractions for model deployment, ensuring workflows run efficiently and are easily adaptable to future use cases. β’ Assess, provision, monitor, and maintain the appropriate infrastructure and tooling to execute model training and prediction workflows. β’ Create visualizations using dashboards or application development frameworks to deliver data insights to our clients. β’ Collaborate and communicate effectively in a distributed work environment, contributing to a dynamic and innovative team. β’ Engage in rotating platform support duties, ensuring the reliability and performance of our machine learning systems.
β’ Demonstrated experience in software design and development, with a strong foundation in machine learning, statistics, optimization, and simulation. β’ Hands-on experience developing and deploying machine learning models in cloud-based environments, with distributed computing expertise. β’ Fluency in Python (preferred), with experience in R or other statistical programming languages. β’ Familiarity with front-end development languages such as Javascript or Typescript, along with UI frameworks like React or Vue, is a plus. β’ Proficiency in working with relational databases and SQL, optimizing data management in large-scale systems. β’ Experience working with Linux servers in virtualized or distributed environments, ensuring stable and secure operations. β’ Strong problem-solving skills, with the ability to adapt to evolving technical landscapes and workflows.
β’ Comprehensive benefits plan, including medical, dental, vision, disability, life insurance, paid time off, and a retirement/pension contribution plan. β’ Financial security through competitive compensation and incentives. β’ Additional educational opportunities via Range can be used for courses, conferences, and other options. β’ Company equity. β’ 100% remote-optional work setting.
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