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Disney Entertainment and ESPN Product & Technology is seeking a Principal Machine Learning Engineer to own the architecture and strategic direction of the N&E ML Platform across a large, complex problem space. You will drive step-function improvements in personalization, recommendations, and ML infrastructure, partnering with senior leadership and cross-org teams to set the standard for ML excellence.
You will mentor engineers, drive reliability, and align ML initiatives with business outcomes
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.
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.
Basic Qualifications
Bachelor’s degree in computer science, Information Systems, Statistics, Math, or comparable field of study, and/or equivalent work experience
10+ years of experience building and operating ML engineering systems in production environments, with a track record of owning large, complex problem spaces
Deep expertise in data science, deep learning algorithms, and statistical methods applied to real‑world, large‑scale engineering problems
Demonstrated experience owning architecture across a significant platform or product domain - including authoring architecture documents, driving reviews, and leading implementation
Proven ability to drive quantifiable improvements in ML platform capabilities, personalization quality, or recommendation system performance
Experience designing and evolving backend microservices for large‑scale distributed systems using REST
Strong expertise with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize)
Deep hands‑on experience with big data technologies such as Databricks, Spark, Kinesis, and Kafka
Experience leading incident response for high priority incidents and driving reliability programs across a team or platform
Active participation in cross‑organizational engineering communities, standards‑setting, and architectural governance
Proven track record as a metrics‑driven technical leader who connects engineering decisions to business outcomes
Exceptional communication, influence, and collaboration skills — comfortable presenting to and aligning senior leadership and cross‑functional stakeholders
Experience working in Agile/Scrum environments with strong prioritization and stakeholder management skills
The hiring range for this position in Glendale, California is $207,400 - $278,100 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job‑related knowledge, skills, and experience among other factors. A bonus and/or long‑term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
Product Engineering
Primary Business: PE - Streaming Backend
Primary Job Posting Category: Machine Learning
Employment Type: Full time
Primary City, State, Region, Postal Code: Glendale, CA, USA
Alternate City, State, Region, Postal Code: USA - NY - 7 Hudson Square
Date Posted: 2026-08-21
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