Machine Learning Engineer
Netflix
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
NOTE: This job posting is inclusive of a variety of positions within our Algorithms 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.
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 Algorithms team. 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:
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.
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.