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 Member Lifecycle and Monetization Data Science & Engineering team plays a critical role for Netflix in driving and accelerating sustainable growth of members and revenue globally, by leveraging data, experimentation & machine learning to develop compelling and persuasive conversion and monetization experiences post-signup to optimize revenue per member.
Machine Learning in these areas is a relatively greenfield area, and comes with the potential for 0-1 applications that can drive millions of dollars of impact at Netflix’s scale. We are looking for a research engineer to join the team to contribute to operating, as well as innovating on growth and commerce algorithms in production, validating through running offline experiments, and building online A/B tests to run in production systems.
You’ll partner with other ML engineers, scientists and product managers on cross-functional ML initiatives. To excel in this role, you should have experience with large-scale applications involving machine learning, a good sense of software engineering principles and design, possess strong communication skills, and the ability to work well in large cross-functional teams. In this role, you will: * Design, implement and operate high impact machine learning models * Partner closely with cross-functional teams, including researchers, engineers, data scientists, and product managers, to identify high value applications of machine learning, translating business intuition into data-driven solutions * Work closely with scientists and engineers to create scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment in Netflix's large-scale, real-time systems. * Contribute to the development of better infrastructure for developing and deploying ML models * Advocate for and apply best practices when it comes to availability, scalability, operational excellence, and cost management
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Netflix is a streaming service that offers a wide variety of TV shows, movies, documentaries, and more. They are known for their original content and their global reach.