Disney Internship – Machine Learning Research

Job Summary

Disney Research Labs invites passionate and innovative individuals to join our Machine Learning Research Internship program. This internship offers a unique opportunity to work at the forefront of AI and machine learning technologies, contributing to cutting-edge projects that influence Disney’s digital media, entertainment, and research initiatives. Interns will collaborate with world-class researchers and engineers, gaining hands-on experience in developing machine learning models, experimenting with novel algorithms, and applying AI solutions to real-world challenges in media, animation, and interactive entertainment.


Key Responsibilities

  • Assist in designing, developing, and implementing machine learning models for diverse research projects.
  • Conduct data analysis, preprocessing, and feature engineering to support model development.
  • Collaborate with cross-functional research teams to explore innovative solutions for real-world problems.
  • Conduct literature reviews and benchmark current research to inform project development.
  • Document research methodologies, experiments, and results for internal and external publications.
  • Present findings and insights to technical and non-technical stakeholders.
  • Stay up-to-date with the latest advancements in AI and machine learning technologies.

Required Skills and Qualifications

  • Currently pursuing a Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Artificial Intelligence, or related fields.
  • Strong understanding of machine learning concepts, algorithms, and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
  • Proficiency in programming languages such as Python, R, or C++.
  • Solid knowledge of statistics, probability, and data analysis.
  • Experience with data visualization tools and techniques.
  • Excellent problem-solving, analytical, and critical thinking skills.
  • Strong written and verbal communication skills.

Experience

  • Prior experience in machine learning research, data analysis projects, or AI-related internships is preferred but not mandatory.
  • Contributions to open-source projects, academic publications, or personal research projects in ML/AI will be an advantage.

Working Hours

  • Flexible working hours, typically 20–40 hours per week depending on the internship program.
  • Remote and on-site options available, depending on eligibility and location.

Knowledge, Skills, and Abilities

  • Ability to work independently and collaboratively in a research-focused environment.
  • Strong organizational skills and attention to detail in documenting experiments and results.
  • Creativity and curiosity in approaching complex problems with innovative solutions.
  • Adaptability to learn new technologies, methodologies, and frameworks quickly.
  • Team-oriented mindset with a passion for contributing to high-impact research projects.

Benefits

  • Hands-on experience with cutting-edge machine learning and AI research.
  • Mentorship from world-class researchers and access to Disney’s extensive research resources.
  • Opportunity to contribute to projects that impact Disney’s global entertainment platforms.
  • Networking opportunities with professionals and researchers across Disney’s technology divisions.
  • Letter of recommendation and potential for future full-time employment.

Why Join

Disney Research Labs is a globally recognized hub for innovation, blending creativity with advanced technology. As a Machine Learning Research Intern, you will be part of a dynamic team pushing the boundaries of AI in entertainment and media. This internship provides a rare opportunity to contribute to high-impact research, develop professionally, and gain exposure to Disney’s culture of innovation and excellence.


How to Apply

  • Submit your updated resume, cover letter, and any relevant research portfolio or project links.
  • Applications are accepted through the Disney Careers portal or the Disney Research Labs internship webpage.
  • Shortlisted candidates may be invited for technical interviews and project-based assessments.
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