Manager, Machine Learning Engineering - Ad Platforms

Manager, Machine Learning Engineering - Ad Platforms

Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally.

The team marries technology with creativity to build world‑class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators, Creators and Builders, Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touchpoints serving millions of people around the world.

• Building the future of Disney’s media: Our technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come.
• Reach, Scale & Impact: Disney+, Hulu, ESPN, ABC, ABC News and many more serve as a signature doorway for fans’ connections with the company’s brands and stories.
• Innovation: We develop and implement groundbreaking products and techniques that shape industry norms and solve complex technical problems.

Ad Platforms organization within Disney Entertainment and ESPN Technology is fully responsible for building, enhancing and maintaining a high‑performance, distributed, microservice‑based advertising platform across all of Disney online properties, including Hulu and ESPN+. We build and maintain proprietary technology ranging from ad serving and delivery, campaign management, reporting, and integrations.

Our mission is to advance AI and machine learning capabilities across Ad Platform by delivering scalable, high‑impact AI/ML and data‑science solutions that enhance various aspects of ad serving. We are seeking a Senior Manager Machine Learning to join this innovative team.

You will apply your battle‑tested experience, deep technical knowledge of software and systems including Machine Learning and AI technologies, and leadership skills to unblock and guide our ML/AI team members to design and build scalable, performant, maintainable, and testable models and pipelines in various domains using industry best practices, in close collaboration with the ML team in the US.

• A willingness and desire to effectively communicate and collaborate across teams and systems on architecture, design, and implementation.
• A passion for mentoring, learning, and taking on new challenges.
• A proven ability to work with product teams to translate requirements into well‑defined technical implementations, and to define technical and operational metrics to measure system health.
• A keen eye for potential optimizations and enhancements.
• Kindness and pragmatic optimism.
• A deep understanding of model development cycles and AI tool usage.

• Lead, mentor and guide Data Scientists, Machine Learning and AI engineers to build solutions adhering to industry best practices and deliver scalable solutions, including model architecture and algorithm selection.
• Lead by example and always strive to improve the design for more scalable, cleaner, and decoupled implementations.
• Drive adoption of best practices in model development, code quality, testing, and documentation.
• Solid understanding and usage of automated tools (AI) while adhering to company policy.
• Define strategic direction for machine learning projects and collaborate with product and engineering stakeholders.
• Oversee end‑to‑end machine learning workflow, including data collection, model development, deployment and modeling, aligned with the larger platform strategy and tools in collaboration with global teams to stay consistent across Ad Platforms.
• Foster innovation by exploring new ML techniques, tools, and technologies.
• Communicate strategies, progress, and results to leadership and cross‑functional teams.
• Ensure responsible AI practices, including fairness, explainability, and compliance with privacy…