Machine Learning Engineer

October 26

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Description

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.

Requirements

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.

Benefits

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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