Engineering Manager, Machine Learning, Content Representation Models (AI Foundations)

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.

The Opportunity

At Netflix innovation in foundation models is redefining how we understand stories and personalize experiences for hundreds of millions of members worldwide. The Content Representation Models (CRM) team sits at the center of this transformation creating unified representations of content that power personalization and discovery across Netflix.

This team develops the embedding models that understand our catalog at every level from rich metadata-based representations (e.g. tags talent synopsis IP) to media-based representations learned directly from video audio and text. Together these representations form the backbone of how we represent content in our algorithms.

As Netflix expands into new content types and formats: from live and interactive experiences to games and podcasts – the need for deeper semantic understanding of our content becomes even more critical. Large vision and language models (VLMs MLLMs and GenAI systems) now make it possible to understand media at a far more nuanced and fine-grained level and this team is bringing those capabilities into the heart of personalization helping our algorithms reason about stories style and audience engagement.

These embeddings are foundational not only to personalization and search but also to applications across Ads Content & Studio Data Science and other business verticals: driving insights optimization and creativity at scale.

We are looking for a seasoned engineering leader to guide this world-class team of ML researchers and engineers. You will lead the evolution of Netflix’s content embedding ecosystem — advancing the science of multimodal and metadata-based representation learning ensuring reliability and adoption in production and partnering to deliver impact.

Questions Your Team Will Help Answer

The Content Representation Models team provides a unified semantically rich representation of content enabling more engaging recommendations and creative insights. Some of the strategic questions the team answers include:

• How can we represent every title episode and clip across video audio text and metadata in a shared embedding space?

• How can unified content representations enable personalization and discovery across Netflix products?

• How do we measure and improve the semantic and engagement quality of our embeddings?

• What foundation architectures (e.g. multimodal LLMs ensemble embeddings) best capture the richness of Netflix content?

• How do we ensure our embedding pipelines are reliable reproducible and production-grade?

In This Role You Will

• Lead a team of researchers and engineers advancing both media-based and metadata-based representations of content.

• Drive innovation in foundation model research leveraging large language and vision-language models to enhance metadata and media understanding and using Netflix’s unique long-form media and engagement data to create richer more personalized representations.

• Ensure production excellence across embedding pipelines – maintaining reliability performance and scalability.

• Guide adoption of embeddings as first-class products partnering with downstream application teams to maximize business and product impact.

Minimum Qualifications

• Proven track record of building and leading high-performing ML research or foundation model teams.

• Experience developing and/or deploying large-scale representation learning multimodal or embedding systems.

• Strong technical judgment in foundation model architecture training evaluation and deployment.

• Experience balancing research exploration with production reliability.

• Strong collaboration and communication skills – able to represent technical work to non-technical partners.

• Demonstrated ability to drive cross-functional adoption of platform-level ML capabilities.

• Advanced degree in Computer Science Machine Learning or a related quantitative field or equivalent practical experience.

Preferred Qualifications

• 8+ years of experience in ML or AI including 3+ years leading technical teams.

• Background in multimodal learning contrastive training or LLM-based embedding architectures.

• Experience building ML systems used across multiple product surfaces.

• Experience with large-scale distributed training embedding infrastructure or evaluation frameworks.

• Familiarity with both research-oriented and production-grade ML workflows.

Culture & Benefits

Netflix's culture is an integral part of our success and we approach diversity and inclusion seriously and thoughtfully. We are an equal opportunity employer and celebrate diversity recognizing that bringing together different perspectives and backgrounds helps build stronger teams. We do not discriminate on the basis of race religion color national origin gender sexual orientation age marital status veteran status or disability status.

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 $190000 - $920000.

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. See more details about our Benefits here .

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 diversitybuilds 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.