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Senior Research Scientist - Machine Learning for Personalization

  • Los Gatos, California
  • Product Engineering
As Netflix continues to grow rapidly around the world, we face new and exciting challenges for our machine learning algorithms to solve so that we can build the perfect homepage for each member. We need to handle the scale and diversity of tastes of people around the world. We need to enable new user interface and interaction paradigms by making sure we use every piece of screen real-estate in an effective manner. We need to balance many factors such as: accuracy and diversity; discovery and continuation; exploration and maximization; recommendations and promotion; immediate engagement and long-term satisfaction. To do this we need to take our machine learning approach for creating the home page to the next level.

The Page Algorithms team is looking for a passionate and talented applied machine learning expert join us. In this role, you will lead the way by researching and developing of the next generation of algorithms used decide what content to show on the Netflix homepage. We are considering some big changes to our approach, so this is an extraordinary time for you to join to have a large impact. For more details about Netflix personalization, see these blog posts: 

As a Research Scientist at Netflix, you will conduct applied research by conceptualizing, designing, implementing, and validating potential algorithmic improvements for the homepage. This includes running offline experiments and building online A/B tests to run in production systems. To be successful in this role, you need a strong machine learning background, solid software development skills, a love of learning, and to collaborate well in multi-disciplinary teams. You will need to exhibit strong communication and leadership skills, an ability to set priorities, and an execution focus in a dynamic environment.

To learn more about our research work, you can visit our research page here.

What we are looking for:

  • 5+ years of research experience with a track record of delivering quality results
  • Expertise in machine learning spanning supervised and unsupervised learning methods
  • Experience in contextual multi-armed bandit algorithms and/or reinforcement learning
  • Experience in successfully applying machine learning to real-world problems
  • Strong mathematical skills with knowledge of statistical methods
  • Strong software development experience in languages such as Scala, Java, Python, C++ or C#
  • Great interpersonal skills
  • PhD or MS in Computer Science, Statistics, or related field

Preferred, but not required, additional areas of experience:

  • Recommendation Systems, Personalization, Search, or Computational Advertising
  • Deep Learning or Causal Inference
  • Optimization algorithms and numerical computation
  • Spark, TensorFlow, or Keras
  • Cloud computing platforms and large web-scale distributed systems