Senior Research Scientist – Algorithms Engineering

Website Netflix

Want to research and develop improvements to the core algorithms such as recommendations and search that power the Netflix experience that over 150+ million members worldwide see each time they log in? Our Algorithms Engineering team is looking for a passionate and talented applied machine learning expert to lead the way by researching and developing the next generation of algorithms for our member experience. This spans central areas of our product including how we approach recommendations, ranking, page generation, image personalization, search, messaging, and marketing.
In this role, 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.
If you are ready to make a difference at a company that matters, and if you want to work on machine learning and data in a company that strongly believes in both, then we would love to talk to you.
For more details about what we are working on, read these blog posts.
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 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:

  • Experience in Recommendation Systems, Personalization, Search, or Computational Advertising
  • Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning in real applications
  • Experience in optimization algorithms and numerical computation
  • Experience with Spark, TensorFlow, or Keras
  • Experience with cloud computing platforms and large web-scale distributed systems
  • Open source contributions

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