Job Description

Responsibilities Think about how to build distributed systems at scale with enterprise-grade security and reliability Drive testing, releases, and monitoring of machine learning based products Write high quality, shippable code across the stack that is easy to maintain and test Collaborate with Applied Science and Product teams to ensure successful and timely delivery of new machine learning products and features Work collaboratively across different time zones and geographies Develop highly scalable and reliable machine learning infrastructure that can perform model training and evaluation. Build vital tools and infrastructure to monitor and understand the performance of complex systems. Basic qualifications Minimum of 12 years of related experience with a bachelor\'s degree; or 8 years of related experience with a master\'s degree; or a PhD with 5 years\' experience; or equivalent experience. Experience building/consuming RESTful and gRPC based web-services Experience with CI/CD build pipelines, integrated tests, and test-driven development Familiarity with cloud deployment technologies, such as Kubernetes or Docker containers Experience with designing and scaling fullstack or distributed backend systems Experience with building carrier grade availability services Preferred qualifications Ideal candidates have past experience building machine learning products, data pipelines, or machine learning training and deployment systems. Experience with deployment and monitoring of machine learning models Ability and desire to move across technology stacks fluently and easily

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