About Netflix

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 Team

The goal of our Content Management & Distribution Data Science and Engineering team is to enable operational and creative excellence in the distribution and promotion of our content on our service. We collaborate closely with our partners in the Product Discovery & Promotion organization, and our work directly contributes to launching high-quality content and helping members discover stories they’ll love.

We conduct analyses, build analytical tools, and develop models that power these objectives.

We are looking for a talented Research Scientist to join our Merchandising & Content Understanding pod. This team focuses on deepening content metadata across all formats and improving the discovery experience on our service.

You will design and develop models and conduct quality evaluations for algorithms powering the next generation of capabilities for our business. You’ll partner with world-class creative production practitioners and cross-functional teams to shape strategy and deliver impact through machine learning and AI solutions.

What You Will Do

• Collaborate closely with stakeholders in Product Discovery & Promotion to deeply understand content metadata and merchandising challenges, identifying high-impact machine learning opportunities.
• Develop innovative systems and models that empower decision-making and power product features that deliver member joy.
• Leverage diverse metadata and production media generated throughout the end-to-end lifecycle of our content.
• Operationalize models so they integrate seamlessly into workflows.
• Serve as a key thought partner to stakeholders and cross-functional teams on ML algorithms and system architectures.

Your Background and Characteristics

• Ph.D. or MS degree in a quantitative or computational field.
• 4+ years of full-time experience in relevant machine learning roles.
• Practical experience in supervised, unsupervised, and deep learning methods.
• Experience applying machine learning and GenAI solutions to video, audio, and/or textual data sources.
• Experience developing quality evaluations (e.g., LLM-as-a-judge, LLM juries).
• Experience operationalizing or productionizing ML/AI solutions.
• Comfortable operating in ambiguous problem spaces with minimal oversight.
• Exceptional written and verbal communication skills for technical and non-technical audiences.

Compensation

Netflix’s compensation structure consists solely of an annual salary — no bonuses. Each year, you choose how much compensation you want in salary versus stock options.

The compensation range for this role is:
$466,000 – $750,000 annually

Compensation varies based on location and is determined using market indicators, job family, background, skills, and experience.

Benefits

Netflix offers comprehensive benefits including:
• Health Plans and Mental Health support
• 401(k) with employer match
• Stock Option Program
• Disability Programs
• Health Savings and Flexible Spending Accounts
• Family-forming benefits
• Life and Serious Injury Benefits
• Paid leave of absence programs

Full-time hourly employees accrue 35 days annually for PTO (vacation, holidays, sick time). Full-time salaried employees receive flexible time off immediately.

Inclusion & Equal Opportunity

Inclusion is a Netflix value. We strive to create a meaningful interview experience for all candidates. If you require accommodation during the hiring process, please contact your recruiting partner.

We are an equal opportunity employer and celebrate diversity. We do not discriminate based on race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

This job posting will remain open for no less than 7 days and will be removed when the position is filled.