Machine Learning Engineer

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 in various genres and languages. Members can play, pause, and resume watching anytime, anywhere, and can change their plans at any time.

The Role

NOTE: This job posting is inclusive of various positions within our Algorithms Engineering group. Based on your background, expertise, and interests, we will direct you to the most appropriate team(s). All teams may not be hiring simultaneously.

As Netflix continues to expand, so does the opportunity to enhance our personalization systems and algorithms. We are seeking a passionate and talented Machine Learning Engineer to join our Algorithms team. In this role, you will leverage your expertise in machine learning and software engineering to design, develop, and scale solutions that enhance 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, from initial concept to deployment in Netflix's large-scale, real-time systems.
• Optimize the performance and scalability of machine learning models to accommodate 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 continuous improvements in our ML infrastructure and tools, ensuring we remain at the industry forefront.
• Engage in continuous learning and development to stay updated with the latest advances in machine learning and software engineering.

What We Are Looking For

• 5+ years of industrial experience in applying machine learning with a track record of impactful results.
• PhD or Master's degree 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, and familiarity with Scala, Java, C++, or C#.
• Experience in one or more applied fields: Recommendations, Personalization, Long-term Reward Modeling, Bandits, Transformers, Large-Scale Language Models, LLM evaluation, RLHF reward modeling/alignment.
• Strong interpersonal skills, including written and verbal communication.

Preferred Qualifications

• Experience in building or enhancing personalization systems, search engines, or other 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 collaborating with cross-functional teams.

Links

Our compensation structure consists solely of an annual salary; we do not offer bonuses. Annually, you can choose 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 job family, background, skills, and experience. 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 leave. 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 build stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate based on race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status