Research Scientist - Content Understanding

Research Scientist - Content Understanding

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

The goal of our Content Management & Distribution Data Science and Engineering team is to enable operational and creative excellence in the distribution and promotion of our content on our service. We collaborate closely with our partners in the Product Discovery & Promotion organization, and our work directly contributes to launching high-quality content on our service and helps our members discover content they will love.

We are looking for a talented Research Scientist - Content Understanding to join our Merchandising & Content Understanding pod, which focuses on deepening our content metadata across all formats and improving the discovery experience on our service. You will design and develop models and conduct quality evaluations for algorithms that will power the next generation of capabilities for our business. You will partner with our world-class team of creative production practitioners and various cross-functional teams to shape strategy and deliver impact via machine learning and artificial intelligence solutions.

What You Will Do

• Collaborate closely with stakeholders in Product Discovery & Promotion to learn deeply about content metadata and merchandising and identify potentially impactful problems to solve via scalable machine learning and artificial intelligence solutions.
• Develop innovative systems and models that empower decision-making for stakeholders and product features that can deliver member joy by leveraging a wide variety of metadata and production media generated by and collected from our productions throughout their end-to-end lifecycle.
• Collaborate with team members and cross-functional partners to operationalize your models so that they can be integrated seamlessly into operational workflows.
• Serve as a key thought partner for stakeholders, cross-functional partners, and our diverse set of team members regarding machine learning algorithms and system architectures.

Your Background And Characteristics

• Ph.D. or MS degree in a quantitative or computational field.
• 4+ years of full-time work experience in one or more relevant machine-learning roles.
• Practical experience in supervised, unsupervised, and deep machine learning methods.
• Practical experience applying machine learning and Gen AI solutions to video, audio, and/or textual data sources, and developing quality evaluations via mechanisms such as LLM-as-a-judge or LLM juries.
• Practical experience operationalizing or productionizing machine learning and/or artificial intelligence solutions.
• Comfortable and effective in ambiguous problem spaces; ability to own and drive projects with minimal oversight and process.
• Exceptional written and oral communication with technical and non-technical audiences.

Key skills/competency

• Machine Learning
• Artificial Intelligence
• Deep Learning
• Content Understanding
• Data Science
• Algorithm Development
• Metadata Analysis
• Gen AI
• Model Operationalization
• Product Discovery