Principal Machine Learning Architect (L7) - Content Promotion & Distribution

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.

Content Promotion & Distribution operates where studio capabilities meet member experience. Our team is at the forefront of transforming how we catalog, promote, localize, and distribute content. We’re seeking a Principal-level individual contributor with deep technical expertise, a strategic vision for scalable, high-quality AI systems, and a strong track record of delivering meaningful impact.

In this rare opportunity, you will help shape the future of content promotion and distribution by leveraging AI, and by building end-to-end agentic solutions that streamline and evolve complex workflows, unlocking entirely new products and experiences. If you’re passionate about building the next wave of AI technology and want to make a lasting impact on how Netflix distributes and promotes content, we’d love to talk with you.

Responsibilities

• Serve as a domain expert and thought leader, shaping the technical vision by identifying high-impact opportunities and bringing solutions to complex business problems across the content product ecosystem.

• Lead the design and development of the ML/AI architecture of Netflix’s Content Promotion & Distribution, spanning agentic solutions, multimodal media understanding, and generation. 

• Partner with Netflix’s platform teams to define, prioritize, and champion high‑leverage capabilities by translating technical architecture needs into concrete platform and infrastructure requirements.

• Partner with engineering teams to design end-to-end ML data foundations for efficient, reliable multimodal data annotation, processing, and storage, and to design and implement algorithm and workflow observability and telemetry.

• Help define rigorous and scalable evaluation frameworks, leveraging offline/online evals, A/B testing, and human-in-the-loop reviews.

• Help de-risk new initiatives through hands-on discovery, prototyping, and scoping.

• Lead the design of horizontal foundational capability layers that scale across use cases, connecting dots across verticals and replacing siloed builds with shared paved paths.

About You

• Proven track record of designing and productionizing advanced AI systems that integrate capabilities across vision, text, audio, and video modalities.

• MS or PhD in ML, Computer Science, or related fields.

• Significant experience in building, deploying, and evaluating robust agentic systems in production environments.

• Comfortable with ambiguity and minimal process, able to take ownership and independently lead projects

• Skilled at establishing strong partnerships with a diverse range of cross-functional teams, fostering collaboration and alignment.

• Ability to inspire, mentor, and guide team members and stakeholders without relying on formal authority.

• Passionate about staying at the forefront of AI advancements and contributing to the broader AI community.

• Netflix culture resonates with you.

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.