In this role, you will contribute to building, implementing, and scaling the next generation of personalization algorithms using techniques such as causal inference, machine learning, reinforcement learning, and econometrics. You will work with a team of experts in these techniques to understand how members experience titles, and how that changes their long-term assessment of their satisfaction with the Netflix service. You will be responsible for operating, as well as innovating, these algorithms in production. You will conduct applied research by conceptualizing, designing, implementing, and validating potential algorithmic improvements. This includes researching and applying cutting-edge machine learning algorithms, running offline experiments, and building online A/B tests to run in production systems. You will partner with people from many disciplines, including behavioral scientists, machine learning researchers, and application engineers
Requirements:
A burning desire to solve real-world problems at scale by applying Machine Learning; PhD or Masters in Computer Science, Statistics, or any of the related fields; Experience with large-scale, real-world machine-learning applications; Experience in machine learning, causal inference, reinforcement learning, and econometrics; Strong mathematical skills with knowledge of statistical methods; Excellent software engineering skills in languages such as Scala, Java, Python, C++ or C#; Experience with machine learning libraries TensorFlow, PyTorch, JAX, or Keras; Experience with large-scale data frameworks such as Spark, Flink, Hive, or Hadoop; Solid understanding of various software engineering best practices and their appropriate application
Text:
Machine Learning Engineer, Algorithms Engineering In this role, you will contribute to building, implementing, and scaling the next generation of personalization algorithms using techniques such as causal inference, machine learning, reinforcement learning, and econometrics. You will work with a team of experts in these techniques to understand how members experience titles, and how that changes their long-term assessment of their satisfaction with the Netflix service. You will be responsible for operating, as well as innovating, these algorithms in production. You will conduct applied research by conceptualizing, designing, implementing, and validating potential algorithmic improvements. This includes researching and applying cutting-edge machine learning algorithms, running offline experiments, and building online A/B tests to run in production systems. You will partner with people from many disciplines, including behavioral scientists, machine learning researchers, and application engineers A burning desire to solve real-world problems at scale by applying Machine Learning; PhD or Masters in Computer Science, Statistics, or any of the related fields; Experience with large-scale, real-world machine-learning applications; Experience in machine learning, causal inference, reinforcement learning, and econometrics; Strong mathematical skills with knowledge of statistical methods; Excellent software engineering skills in languages such as Scala, Java, Python, C++ or C#; Experience with machine learning libraries TensorFlow, PyTorch, JAX, or Keras; Experience with large-scale data frameworks such as Spark, Flink, Hive, or Hadoop; Solid understanding of various software engineering best practices and their appropriate application
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