As Netflix continues to grow, we are venturing into exciting new frontiers of personalization to help our members find the content they’ll most enjoy. We seek to give each TV show and movie its best opportunity to appeal to our members by personalizing how it is displayed on Netflix its showcased image assets, trailers, metadata, explanations, etc., which we broadly refer to as “evidence”. This allows us to provide each member with the most useful information for them when deciding what to watch. This is increasingly important as we launch hundreds of brand-new titles that members may only learn about through the recommendations served through our service.
We are looking for a leader for the nascent Evidence Personalization Algorithms Engineering team. You will lead the way for a small team of machine learning researchers and engineers to develop the next generation of algorithms used to generate and select artwork, trailers, metadata, and other evidence shown on Netflix. The team has taken its first few steps into this exciting space that has the opportunity to shape much of what our members see across our user experience. This starts with artwork personalization but extends to many different forms of evidence that we can display and to the process of creating the evidence assets themselves. This area touches on a broad set of machine learning areas spanning recommender systems, computer vision, natural language processing, and bandit algorithms.
In this role you will be responsible for building and leading a team of world-class researchers and engineers doing cutting-edge applied machine learning. You will help select and guide projects from end-to-end idea to production A/B tests. You will partner with many disciplines, including asset creation experts, application engineers and user interface teams. Your team will be responsible for the production algorithms, innovating on them, and developing new ones. To be successful in this role, you need a strong machine learning background, to be a quick learner, data-driven, have a passion for personalization, have proven software engineering and system design skills, and the ability to lead large multi-disciplinary, cross-functional teams. You also need to be great at giving and receiving feedback, championing new ideas, empowering others, and balancing the needs of both research and engineering.
What We Are Looking For
Experience building and leading a high-performing team of researchers and engineers
Ability to lead in alignment with our unique culture
Strong communication skills and the ability to partner with teams spanning many disciplines
Broad knowledge of machine learning with strong foundation in mathematical and statistical methods
Experience successfully applying machine learning to real-world problems
Experience leading software engineering efforts for production-scale systems
Great interpersonal skills
MS (PhD preferred) in Computer Science, Statistics, or a related field
Preferred, But Not Required, Additional Areas Of Experience
Recommendation Systems, Personalization, or Computer Vision
Bandits or Reinforcement Learning
Deep Learning or Causal Inference
Java, Scala, and Spark
TensorFlow, Keras, and PyTorch
Netflix is the world’s leading Internet television network with over 62 million members in nearly 50 countries enjoying more than two billion hours of TV shows and movies per month, including original series, documentaries and feature films. Members can watch as much as they want, anytime, anywhere, on nearly any Internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.