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Home›Jobs›Netflix›Machine Learning Engineer, AI for Member Systems
Netflix

About Netflix

The streaming service redefining entertainment worldwide

🏢 Tech, Media👥 10K-50K📅 Founded 1997📍 Los Gatos, California, United States

Key Highlights

  • Over 238 million subscribers across 190 countries
  • Headquartered in Los Gatos, California
  • Valued at over $150 billion
  • Offers a vast library of original content and films

Netflix, headquartered in Los Gatos, California, is a leading streaming service with over 238 million subscribers globally. The platform offers a vast library of movies, TV shows, and original content, including award-winning series like 'Stranger Things' and 'The Crown.' With a market valuation exc...

🎁 Benefits

Employees enjoy competitive salaries, stock options, unlimited PTO, and comprehensive health benefits. Netflix also offers a flexible remote work poli...

🌟 Culture

Netflix fosters a culture of freedom and responsibility, encouraging employees to take risks and make decisions independently. The company values tran...

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Netflix

Machine Learning Engineer, AI for Member Systems

Netflix • USA - Remote

Posted 1 year ago🏠 RemoteMachine learning engineer📍 United states
Apply Now →

Job Description

Netflix is one of the world's leading entertainment services, with over 300 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.

As Netflix continues to grow, so do the opportunities to enhance our personalization systems and algorithms. We're looking for a passionate and talented Machine Learning Engineer to join our Al for Member Systems. In this role, you will apply your expertise in machine learning and software engineering to design, develop, and scale solutions that power the Netflix experience.

Key Responsibilities:

  • Collaborate with cross-functional teams, including researchers, engineers, data scientists, and product managers, to develop and implement machine learning algorithms that improve personalization, recommendations, and member experiences.

  • Create scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment in Netflix's large-scale, real-time systems.

  • Optimize the performance and scalability of machine learning models, ensuring they can handle the diverse tastes and behaviors of our global member base.

  • Design and conduct offline experiments and A/B tests to validate the impact of algorithmic changes on key business metrics.

  • Contribute to the ongoing improvement of our ML infrastructure and tooling, ensuring that we stay at the cutting edge of industry practices.

  • Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning and software engineering.

What we are looking for:

  • 5+ years of experience in applying machine learning in an industrial setting, with a track record of delivering impactful results.

  • PhD or Masters in Computer Science, Statistics, or a related field

  • Expertise in machine learning algorithms and frameworks, with hands-on experience in training, tuning, and deploying models in production environments.

  • Excellent software design and development skills in Python along with Scala, Java, C++, or C#

  • Experience in one or more of the following applied fields: Recommendations, Personalization, Long-term Reward Modeling, Bandits, Transformers, Large-Scale Language Models, LLM evaluation, RLHF reward modeling/alignment

  • Great interpersonal skills including strong written and verbal communication

Preferred Qualifications:

  • Experience building or enhancing personalization systems, search engines, or similar large-scale machine learning applications.

  • Background in neural networks, natural language processing, or causal inference

  • Contributions to open-source projects in machine learning or related fields.

  • Experience working with cross functional teams

Links:

  • Netflix Research site

  • Our culture

  • Our long term business view

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 $100,000 - $720,000.

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.

NOTE: This job posting is inclusive of a variety of positions within our AI for Member Systems (AIMS) Engineering group. Based on your background, expertise and interests, we will route you to the appropriate team(s). All teams may not be hiring at the same time.

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.

Interested in this role?

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