Machine Learning Engineer - Content Management & Distribution

June 5

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Netflix

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B2C • eCommerce • Media

Netflix is a global streaming service that offers a wide variety of award-winning television shows, movies, anime, documentaries, and more on thousands of internet-connected devices. It allows users to watch instantly and provides original content produced by Netflix itself, catering to diverse tastes. As a pioneer in original programming since its first series in 2013, Netflix aims to entertain audiences worldwide through immersive storytelling and innovative technology.

- employees

Founded 1997

👥 B2C

🛍️ eCommerce

📱 Media

💰 $20M Post-IPO Equity on 2022-01

📋 Description

• Collaborate closely with stakeholders in Product Discovery & Promotion to learn deeply about content metadata and merchandising and identify potentially impactful problems to solve via scalable machine learning and artificial intelligence solutions • Develop innovative systems and models that empower decision-making for stakeholders and product features that can deliver member joy by leveraging a wide variety of metadata and production media generated by and collected from our productions throughout their end-to-end lifecycle • Collaborate with team members and cross-functional partners to operationalize your models so that they can be integrated seamlessly into operational workflows • Serve as a key thought partner for stakeholders, cross-functional partners, and our diverse set of team members regarding machine learning algorithms and system architectures

🎯 Requirements

• Ph.D. or MS degree in a quantitative or computational field • 4+ years of full-time work experience in one or more relevant machine-learning roles • Practical experience in supervised, unsupervised, and deep machine learning methods • Practical experience applying machine learning and Gen AI solutions to video, audio, and/or textual data sources • Practical experience operationalizing or productionizing machine learning and/or artificial intelligence solutions • Comfortable and effective in ambiguous problem spaces; ability to own and drive projects with minimal oversight and process • Exceptional written and oral communication with technical and non-technical audiences