Research Scientist (L5) - Product Machine Learning Research

Key Skills

Computer Vision (CV), Effective communication skills, Machine learning techniques, Natural Language Processing (NLP), Reinforcement Learning, Statistics

Job Description

Netflix is one of the world's leading streaming entertainment services with 231 million paid memberships in over 190 countries enjoying TV series, documentaries, feature films and mobile games across a wide variety of genres and languages. Members can play, pause and resume watching as they want, anytime, anywhere, and can change their plans at any time. As Netflix continues to grow, we are venturing further into exciting new innovations in personalization, discovery, experimentation, backend operations, and more, all driven by research at the frontiers of ML.

The Product Machine Learning Research team is an applied research team designed to build up Netflix’s ML capabilities by diving deep and exploring technical opportunities aligned with the biggest challenges at Netflix, and partnering with teams across the business to bring these capabilities to life. As a Senior Researcher on the Product Machine Learning Research team, you will have the opportunity to drive and execute bleeding-edge research in a variety of topics (examples include but are not limited to recommender systems, causal inference, fair and reliable ML) while working in close partnership both with other researchers in the team and with partners in a wide range of product teams. You will develop expertise in the frontiers of ML, influence the direction of company roadmaps, and work cross-functionally with engineering and product to prototype, test, and implement your research in order to deliver improvements to the member experience and drive change across the company. Additionally, you will also be actively engaged with the broader ML research community through publications, organizational activities, and academic collaborations.

We are looking for an experienced researcher that can establish and execute a strong research agenda, disseminate knowledge and get others behind their ideas, and foster an open environment of collaboration, innovation, and intellectual excitement.

What you bring

• Ample ML research experience, in academia or industry, in fields such as recommender systems, causal inference, machine cognition (e.g., NLP, CV), fairness, explainability, statistical learning, reinforcement learning, optimization, operations research, algorithmic game theory, or economics and computation
• A track record of leading ambitious research projects inspired by real-world challenges
• Passion for collaboration and for building solid relationships with colleagues and stakeholders to tackle big, cross-functional problems
• Exceptional communication with both technical and non-technical audiences 
• Self-motivated to build, with an ability to thrive with minimal oversight and process
• Ph.D. in a relevant area

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.

To learn more about our work, visit our research page.

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 $150,000 - $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.