Research/Engineering Manager, Machine Learning for Experience Personalization

Netflix

Los Gatos, CA, USA

Full time

Engineering

May 11

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 make a personalized user experience that adapts to the needs of each of our members around the world. This means going beyond just what is recommended to personalize how we display the recommendations and the way a member interacts with the user experience. Through this we want to provide each member with the best possible version of Netflix for them instead of a one-size-fits-all experience.

We also seek to give each movie, game or TV show its best opportunity to appeal to our members by personalizing how it is displayed on Netflix: its artwork, trailers, metadata, explanations, etc. This allows us to provide each member with the most useful information for them when deciding what to watch and the confidence they’re making a good decision for how to spend their time.


We are looking for a manager to lead the Experience Personalization Algorithms Engineering team. In this role, you will lead the way for a team of machine learning researchers and engineers to develop the next generation of algorithms used to generate and select user experience modules, menus, artwork, trailers, metadata, and other assets shown on Netflix. This includes personalizing how we display recommendations to our members to help them find the best movie, TV show, or game (see this article for an example). This area focuses on machine learning areas around recommender systems, and bandit algorithms but also can include some elements of computer vision and natural language processing.


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 people from many disciplines, including user experience designers, asset creation experts, application engineers, data scientists, 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 engineering and 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
  • Experience leading 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 mathematical foundation
  • Experience leading successful application of machine learning to real-world problems
  • Experience leading and conducting applied research in machine learning
  • Experience leading software engineering and design efforts for large-scale systems
  • Great interpersonal skills
  • MS or PhD in Computer Science, Statistics, or a related field

You will ideally have experience with:

  • Recommendation Systems, Personalization, Computer Vision, or Search
  • Deep Learning, Bandits, Reinforcement Learning, or Causal Inference
  • Working with UI/UX designers and engineers
  • Java, Scala, Python
  • Spark, TensorFlow, Keras
  • A/B testing

Netflix's culture is an integral part of what makes us successful, and we approach diversity and inclusion seriously and thoughtfully. We are an equal opportunity employer and celebrate diversity, recognizing that bringing together different perspectives and backgrounds helps build stronger teams. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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