Senior Research Engineer - Promotion & Growth Algorithms

Job Description

Are you interested in researching new machine learning algorithms to create innovative approaches to a wide range of problems, as well as building large-scale, live-traffic experiments directly impacting and growing our 150+ million members worldwide? The Algorithm Engineering team is looking for a passionate and talented Machine Learning engineer to join us and lead the way in the research and development of the next generation of algorithms used to drive and grow the Netflix experience. To learn more about our research and analytics work, you can visit our research page here.

In this position, you will conduct applied research by investigating, conceptualizing, designing, implementing, and validating new algorithms in a number of areas, such as:
• Finding and growing the best possible audience for newly released movies and TV shows, and in particular our expanding slate of original content. This year, Netflix will invest $6 billion in content and will create original content with great Hollywood talents like Angelina Jolie and Martin Scorsese, and you'll work on the algorithms that help this new content find a great audience.
• Reaching out to our members about new recommendations in the most effective and impactful way, through emails and notifications. We deliver billions of messages per year, and you'll work on the algorithms that decide what to send, when and to whom, to help our members find great content to watch.
• Growing our member base through programmatic advertising. Netflix spends over one billion dollars a year promoting our service and original content. You'll work on new algorithms to maximize our growth that decide what to advertise, to whom, and for how much.

Here are some more examples of what we are working on:
• The Importance of Time and Causality in Recommendations
• Introducing Vectorflow: a lightweight neural network library for sparse data
• The Netflix Recommender System
• Selecting the best artwork for videos through A/B testing
• Recommending for the World

To be successful in this role, you must have a strong machine learning and software engineering background, be a quick learner, and work well in small cross-functional teams. You will need to exhibit strong leadership and communication skills, an ability to set priorities, and thrive 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.

Requirements:
• At least five years of applied research experience with a successful track record of delivering quality results.
• Strong machine learning and algorithmic background with a broad understanding of: supervised and unsupervised learning methods, bandits and reinforcement learning, deep learning.
• Strong development experience (Scala, Java, Python, C++ or similar).
• Great communication skills.
• MS (PhD preferred) in Computer Science, Statistics, or related field.

Preferred, but not required:
• Experience in recommendation systems or computational advertising.
• Experience in optimization algorithms and numerical computation.
• Experience with big data platforms and large distributed systems.

Jobcode: Reference SBJ-r1kwxg-3-141-202-54-42 in your application.