Job description

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 What you’ll bring: • A degree in Computer Science or a related field • 4+ 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. Generally, 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 $466,000.00 - $750,000.00. This compensation range will vary based on location. 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. See more details about our Benefits here . Netflix is a unique culture and environment. Learn more here . Inclusion 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.

Requirements

Must-haves

Design, implement and operate high impact machine learning models
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
A degree in Computer Science or a related field
4+ 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.
Netflix is a unique culture and environment. Learn more here .
Job is open for no less than 7 days and will be removed when the position is filled.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmljavapython

Platform: eightfold
Effort: medium

Benefits

Benefits detected in the listing.

401(K)

Paid Time Off