Research Engineer (L4) - Member Lifecycle and Monetization

Netflix is one of the world's leading entertainment services, with 283 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 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

What you’ll bring:

• A degree in Computer Science or a related field 

• 2+ years of full time engineering experience 

• Curious, self-motivated, and excited about solving open-ended challenges at Netflix.

• Excellent software design and development skills in multi-language settings with Scala, Java, and Python and software engineering best practices (e.g. version control, testing, code review, etc.)

• Exceptional communication skills, able to explain complex technical concepts clearly to cross-functional partners 

• Broad understanding of core machine learning concepts and their application in large-scale, real-world machine-learning systems

• Familiarity end-to-end machine learning pipelines (e.g. training or production deployment) and common challenges like explainability.

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 $150,000 - $750,000.

is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity 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.