As a Principal Machine Learning Engineer, you will drive the development and implementation of the cutting-edge machine learning algorithms, collaborating with business, engineering, and analytics teams, to build large-scale recommendation systems to recommend the best content, notifications and actions to our customers. Your daily responsibilities will encompass a broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations, and providing guidance to emerging ML engineers. Your role is pivotal, stretching beyond these tasks, ensuring AI/ML's transformative potential is realized across our offerings
Requirements:
Master or PhD in a quantitative subject (Statistics, Mathematics, Computer Science, Operations Research, or relevant work experience); 8+ years of related industry experience in the machine learning domain; Expertise in Python with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, Databricks); Experience building and scaling machine learning models in business applications using large amounts of data
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Principal Machine Learning Engineer As a Principal Machine Learning Engineer, you will drive the development and implementation of the cutting-edge machine learning algorithms, collaborating with business, engineering, and analytics teams, to build large-scale recommendation systems to recommend the best content, notifications and actions to our customers. Your daily responsibilities will encompass a broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations, and providing guidance to emerging ML engineers. Your role is pivotal, stretching beyond these tasks, ensuring AI/ML's transformative potential is realized across our offerings Master or PhD in a quantitative subject (Statistics, Mathematics, Computer Science, Operations Research, or relevant work experience); 8+ years of related industry experience in the machine learning domain; Expertise in Python with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, Databricks); Experience building and scaling machine learning models in business applications using large amounts of data
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