Netflix is one of the world’s leading entertainment services with 278 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.
The Role
With over a quarter billion members in over 190 countries and a billion hours of streaming each month, Netflix is the world’s leading online entertainment company. Netflix continues to shape the future of entertainment by developing personalized ways for members to discover and enjoy a rapidly expanding catalog of content.
The Machine Learning & Inference Research (MLIR) team works on core methodological development in areas of strategic importance to Netflix and translates this research into actionable impact by partnering with other teams (e.g. data science, engineering, design, product). MLIR engages with the external research community spanning ML/AI, statistics, economics, and operations research through conferences, academic collaborations, and publications. At the same time, it engages with the internal Netflix community by disseminating research learnings, advising on the incorporation and practical implementation/scalability of new methods and technologies and partnering on translational applied research with direct impact to Netflix product and content priorities. In success, the MLIR team’s expertise and foundational research influences and steers a growing number of projects and roadmaps and cultivates and advances in-house world-class expertise.
What you’ll do
We are seeking an experienced leader to define and execute a strategy that brings cutting-edge methods and holistic thinking to Netflix. The leader must balance a portfolio of foundational/methodological developments spearheaded by the team and collaborative projects with stakeholder teams that directly benefit from these developments. Such collaborations span applied research (such as exploring innovations to the member experience or analyzing Netflix data for actionable insights), devising ambitious yet technically feasible innovation roadmaps, and helping craft technical approaches to advance these roadmaps. To be successful, the leader must be deeply familiar with the business needs, adept at translating these needs into a long-term research agenda, galvanize other teams around this agenda, and committed to fostering an open environment of collaboration, innovation, and intellectual excitement.
Specifically, you will:
We’re looking for
Our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $610,000 – $1,870,000.
Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity of thought and background builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
Job is open for no less than 7 days and will be removed when the position is filled.
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