Machine Learning Engineer (L5) - Content Management & Distribution

Netflix, a global entertainment leader with 300M+ subscribers, is seeking a Machine Learning Engineer (L5) for their Content Management & Distribution team. This role is crucial in enabling operational and creative excellence in content distribution and promotion across Netflix's vast library.

The position sits within the Merchandising & Content Understanding pod, focusing on enhancing content metadata and improving discovery experiences. You'll be at the forefront of developing next-generation algorithms and infrastructure that directly impact how millions of users discover and enjoy content on Netflix.

As an ML Engineer, you'll collaborate with Product Discovery & Promotion stakeholders to identify and solve complex problems using cutting-edge ML and AI solutions. Your work will involve developing innovative systems that leverage various metadata and production media, directly contributing to member satisfaction and content discovery optimization.

The role requires a strong technical background with at least 4 years of ML experience and advanced education in a quantitative field. You'll need expertise in supervised, unsupervised, and deep learning methods, particularly with video, audio, and textual data. The ability to operationalize ML solutions and communicate effectively with both technical and non-technical stakeholders is crucial.

Netflix offers a unique compensation structure where you can choose your preferred mix of salary versus stock options annually, with a competitive range of $150,000 - $750,000. The company promotes a strong culture of inclusion and innovation, offering the opportunity to work remotely while impacting entertainment experiences for millions globally.

This role is perfect for someone who thrives in ambiguous problem spaces, can drive projects independently, and wants to shape the future of content discovery at one of the world's leading entertainment companies. You'll be part of a world-class team, working on challenging problems at scale while helping Netflix maintain its position as an innovation leader in the streaming industry.