Principal Machine Learning Engineer

Job Posting

Title:

Principal Machine Learning Engineer Req :

Job Description:

Disney Entertainment and ESPN Product & Technology 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 touch points 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:
  More than ever, Disney’s technology and products serve as a signature doorway for fans' connections with the company’s brands and stories. Disney+. Hulu. ESPN. ABC. ABC News…and many more. These products and brands – and the unmatched stories, storytellers, and events they carry – matter to millions of people globally.
• Innovation:
  We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems.

As a Principal Machine Learning Engineer, you will define and own the technical architecture and strategic direction of the N&E ML Platform across a large, complex problem space spanning Disney's News & Entertainment portfolio. You will drive step‑function improvements in personalization, recommendation systems, and ML infrastructure - not just at the feature level, but across entire product and platform domains. You will serve as a thought leader who bridges business objectives and technical execution, partnering with senior leadership, product, and cross‑org engineering communities to set the standard for ML excellence within News & Entertainment.

Your impact will be measured by the quantifiable outcomes you drive for our guests and the durable technical foundations you build for the teams around you.

• Focus on major areas of work, typically 20% or more of role
• Architecture Ownership:
  Define and own the end‑to‑end architecture of the N&E ML platform across a large problem space spanning ABC News, ABC Entertainment, National Geographic, Marvel, and Disney Studios. Author architecture documents, drive them through review, and oversee implementation to ensure solutions are scalable, reliable, and aligned with platform‑wide standards.
• Strategic Technical Leadership:
  Identify, scope, and prioritize the most impactful and time‑sensitive ML work streams across the N&E portfolio. Break down and sequence complex initiatives, proactively surface risks to leadership, and drive outcomes with a clear metrics‑driven mindset.
• ML Platform & Infrastructure:
  Drive the design and evolution of infrastructure supporting the full ML lifecycle across diverse content types and brands: data pipelines, workflow orchestration, feature stores, batch training, and low‑latency online serving. Champion reliability, quality, and operational excellence across the platform.
• Innovation & Industry Awareness:
  Stay at the forefront of industry trends in ML, AI, and data engineering. Proactively identify and champion the adoption of new technologies, frameworks, and patterns that drive improvement across the N&E portfolio (e.g. recommendation systems, LLMs, RAGs, object detection, autogenerated content tagging).
• Incident & Reliability Ownership:
  Own and speak to production incidents during weekly meetings with leadership. Hold the team to the right engineering processes and drive a culture of reliability, observability, and continuous improvement across the N&E ML…