Research Scientist / Engineer L4 / L5, Algorithm Engineering

Job Description

NOTE: This job posting is inclusive of a variety of positions within our Algorithms Engineering group. Based on your background, expertise and interests, we will route you to the appropriate team(s).

Members can watch videos and play games as much as they want, anytime, anywhere, on any internet-connected screen.

To achieve our mission of entertaining the world, we are reinventing entertainment from end to end. We are revolutionizing how shows, movies, and games are produced, pushing technological boundaries to efficiently deliver streaming video at massive scale over the internet, and continuously improving the discovery and personalization of our offerings to our global user base using Machine Learning and data analytics.

Applied Machine Learning Research at Netflix improves various aspects of our business, including personalization, recommendations, search, content understanding, messaging, targeting, new member acquisition etc. As such, our research spans many Machine Learning areas, including deep learning, search and recommender systems, causal inference, reinforcement learning and bandits, computer vision, computer graphics, natural language processing, and computational advertising.

We are looking for exceptional individuals to work full time with us as research scientists. In this role, you will conduct applied research by conceptualizing, designing, implementing, and validating potential algorithmic improvements. This includes researching and applying cutting edge machine learning algorithms, 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, a passion for solving end-user problems 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.

What we are looking for:
- A burning desire to solve real world problems at scale by applying Machine Learning
- PhD or Masters in Computer Science, Statistics, or any of the related fields
- 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
- Exceptional problem solving skills
- Strong mathematical skills with knowledge of statistical methods
- Excellent software engineering skills in languages such as Scala, Java, Python, C++ or C#
- Great interpersonal skills
- Strong written and verbal communication skills

Preferred, but not required:
- Experience as a technical leader
- Experience working with cross functional teams
- Experience in Search, Recommendations, Natural Language Processing, Knowledge Graphs, Conversational Agents, and Personalization, etc
- Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning in real world applications
- Experience with Spark, TensorFlow, Keras, and PyTorch
- Experience with cloud computing platforms and large web-scale distributed systems
- Experience in applied research in industrial settings
- Open source contributions
- Research publications at peer reviewed journals and conferences on relevant topics

Links:

Netflix Research site
Our culture
Our long term business view

At Netflix, we carefully consider a wide range of compensation factors to determine your personal top of market. We rely on market indicators to determine compensation and consider your specific job family, background, skills, and experience to get it right. These considerations can cause your compensation to vary and will also be dependent on your location.

The overall market range for roles in this area of Netflix is typically $90,000 - $900,000.

This market range is based on total compensation (vs. only base salary), which is in line with our compensation philosophy. Netflix is a unique culture and environment. Learn more here.

Jobcode: Reference SBJ-g4m0wz-3-145-169-85-42 in your application.