Machine Learning Engineering Intern, Summer 2026

About the Role & Program

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.

Here are a few reasons why we think you’d love working here: 

• 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. 

Product Engineering is a unified team responsible for the engineering of Disney Entertainment & ESPN digital and streaming products and platforms. This includes product engineering, media engineering, quality assurance, engineering behind personalization, commerce, lifecycle, and identity.

Job Summary: As a Machine Learning Engineering Intern on the ESPN Personalization team, you’ll contribute to the next‑generation streaming platform by helping prototype and productionize ML components that personalize short‑form and live sports video experiences in real time. You’ll work alongside senior MLEs to build features, run experiments, and improve recommendations that serve millions of users.

What You Will Do

• Implement data preparation and feature engineering pipelines that feed real‑time recommendation models (batch and streaming).

• Build and evaluate model prototypes (e.g., retrieval, ranking, sequence/embedding‑based approaches) using PyTorch; document findings and trade‑offs.

• Contribute to online/offline experimentation: define metrics, run A/B tests, analyze results, and suggest next steps.

• Integrate model or feature updates into serving paths in partnership with platform engineers; add safeguards/monitors for data and model drift.

• Explore user interaction data to uncover opportunities that improve relevance, latency, and overall user experience.

• Collaborate with product, data science, and infra partners; communicate progress and learnings clearly in code reviews and demos.

Required Qualifications & Skills

• Proficiency with Python and core data tooling (e.g., pandas/NumPy); familiarity with SQL.

• Coursework or hands‑on experience in machine learning (supervised learning, representation learning, model evaluation).

• Exposure to PyTorch and to building/evaluating models in notebooks or scripts.

• Fundamental understanding of data structures, algorithms, and software engineering practices (version control, testing).

• Strong problem‑solving skills, curiosity, and the ability to communicate technical ideas clearly with a cross‑functional audience.

Preferred Qualifications & Skills

• Familiarity with recommendation systems or personalization (retrieval/ranking, embeddings, sequence models/transformers).

• Experience with experimentation platforms and A/B testing concepts; comfort defining and interpreting evaluation metrics.

• Exposure to streaming data and real‑time features (e.g., Kafka, feature stores) or online inference architectures.

• Knowledge of cloud services (AWS/GCP/Azure) and containerization basics (Docker).

• Interest in sports and fan experiences, and how ML can enhance short‑form and live video consumption.

Education

• Junior or Senior year preferred

• Currently enrolled undergraduate student in an accredited college/university, pursuing a Bachelor’s degree in Computer Science, Computer Engineering, Data Science, Machine Learning, or a related field.

Eligibility Requirements & Program Information

Candidates for this opportunity MUST meet all of the below requirements:

• Be enrolled in an accredited college/university pursuing a degree taking at least one class in the semester/quarter (spring/fall) prior to participation in the internship program AND returning to school the semester/quarter following the internship OR currently participating in a Disney College Program or Disney Internship.

• Current Disney Interns, College, International, or Culinary Program Participants:  You may only work for ONE consecutive year (12 months) in any combination of an internship and/or program.  

• Be at least 18 years of age

• Possess unrestricted work authorization

Additional Information  

• Fully available from M-F, 40 hours each week for the entire program duration: May/June - August/September 2026 (12 weeks)

• Able to provide own housing for the duration internship program

• Able to provide/have reliable transportation to/from work

The pay rate for this role in New York, NY or Santa Monica, CA is $42.00 per hour. Select benefits may be provided as part of the compensation package, such as medical, financial, and/or other benefits, dependent on the level and position offered. To learn more about our benefits visit: https://jobs.disneycareers.com/benefits.