Walt Disney
Location
Santa Monica, CA | United States
Job description
SUMMARY
On any given day at Disney Entertainment & ESPN Technology, we’re reimagining ways to create magical viewing experiences for the world’s most beloved stories while also transforming our media business for the future. Whether that’s evolving our streaming and digital products in new and immersive ways, powering worldwide advertising and distribution to enhance flexibility and efficiency, or delivering Disney’s unmatched entertainment and sports content, every day is a moment to make a difference to partners and to hundreds of millions of people around the world.
A few reasons why we think you’d love working here:
Building the future of Disney’s media: DE&E Technologists are designing and building the infrastructure that will power our media, advertising, and distribution businesses for years to come.
Reach & Scale: The products and platforms this group builds and operates delight millions of consumers every minute of every day – from Disney+ and Hulu, to ABC News and Entertainment, to ESPN and ESPN+, and much more.
Innovation: We develop and implement groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment & news.
Platform Software Engineering oversees the core technical platforms and systems for Disney’s massive suite of streaming products – including Disney+ and Hulu – and digital products and experiences – including ESPN, Marvel, Disney Studios, NatGeo, and ABC News. This team also drives the strategic development and use of technology, building scalable systems and products that can power a more personalized experience for Disney customers, as well as innovative work in Augmented Reality (AR), Virtual Reality (VR), and 3D rendering in our studio environments. When you’re watching SportsCenter and you’re impressed by how awesome the studio looks, you have this team to thank!
The Machine Learning (ML) Engineering team at Disney drives and enables ML usage across several domains in heterogeneous language environments and at all stages of a project’s life cycle, including ad-hoc exploration, preparing training data, model development, and robust production deployment. The team is invested in continual innovation of the ML infrastructure itself to carefully orchestrate a continuous cycle of learning, inference, and observation while also maintaining high system availability and reliability. We seek to find new ways to scale with our guest and partner base as well as the ever-growing need for ML and experiments.
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