Want to research and develop improvements to the core algorithms such as recommendations and search that power the Netflix experience that over 130 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, asset selection, search, and messaging.
In this role, you will conduct applied research end-to-end by conceptualizing, designing, implementing, and validating potential algorithmic improvements. 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 leadership and interpersonal 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 and analytics work, you can visit our research page here.
- 5+ years of research experience with a track record of delivering quality results
- Strong background in machine learning with a broad understanding of supervised and unsupervised learning methods
- Strong software development experience in languages such as Scala, Java, Python, C++ or C#
- Successful track record of delivering results in complex cross-functional projects
- Strong mathematical skills with knowledge of statistical methods
- Great interpersonal skills
- MS (PhD preferred) in Computer Science, Statistics, or related field
Preferred, but not required:
- 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