Lead Machine Learning Engineer - Personalization

Company: Disneyland Hong Kong
Location: New York
Posted on: June 1, 2025

Job Description:

Lead Machine Learning Engineer - PersonalizationDisney Entertainment and ESPN Product & TechnologyTechnology 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:1. 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.2. 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.3. Innovation: We develop and implement groundbreaking products and techniques that shape industry norms and solve complex and distinctive technical problems.Job Summary: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.Our team develops and maintains state-of-the-art recommendation and personalization algorithms that serve hundreds of millions of users across Disney+, Hulu, ABC, and ESPN. As a key member of this team, you will collaborate closely with Engineering, Product, and Data teams to apply advanced machine learning techniques in support of strategic personalization initiatives. This is an Individual Contributor role focused on content recommendations. You will lead the research, development, deployment, and optimization of recommendation and personalization algorithms across product surfaces. You will also play a critical role in aligning technical solutions with stakeholder requirements and expectations, partnering with Product, Engineering, and Editorial teams. Beyond execution, you will help define the roadmap for algorithmic innovation-shaping approaches to feature development and contributing to broader company goals in the personalization and recommendation space.Responsibilities and Duties of the Role:

• Developing and prototyping state-of-the-art Deep Neural Net algorithms for recommendation systems
• Deliver a conceptual solution into production-level implementation & operation at scale, for global user services
• Quickly learn our complex streaming recommendation systems and deep dive into individual components & systems as well as understand overall framework/architecture
• Identify impactful opportunities to improve our business operations and develop practical solutions and plans to lift our business KPI's.
• Drive business decisions by data driven and pragmatic approach
• Excellent written and oral communication skills
• Leadership to technically guide a team of engineers and work collaboratively with peers to achieve goals with deadline.Required Education, Experience/Skills/Training:Basic Qualifications:
  • Strong proficiency in at least one of the following deep learning frameworks: TensorFlow, PyTorch
  • Experience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment
  • Track record from design to full production of effective recommendation systems
  • Experience with cloud services in a production environment (particularly AWS)
  • Understanding of statistical concepts (e.g., hypothesis testing, regression analysis)
  • Ability to articulate the usage and behavior of models and algorithms to both technical and non-technical audiences
  • MS or PhD in statistics, math, computer science, or related quantitative field
  • Production experience with developing content recommendation algorithms at scale and familiar with metadata management, data lineage, and principles of data governance
  • Deep understanding of personalization challenges in homepage experience and proven records of developing effective solutionsPreferred qualifications:
    • MS or PhD in statistics, math, computer science, or related quantitative field
    • Experience developing content recommendation algorithms at scale, with familiarity in metadata management, data lineage, and data governance principles
    • Proven track record in personalization challenges for homepage experiences with effective solutionsExperience with:
      • 7+ years of experience in developing highly scalable machine learning products
      • 7+ years of experience writing production-level, scalable Python codeRequired Education:
        • Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or a comparable field, or equivalent work experience#DISNEYTECH------------:DISNEYTECHDisability Accommodation for Employment ApplicationsThe Walt Disney Company and its affiliates are Equal Employment Opportunity employers. If you need a reasonable accommodation during the application process, please visit the Disney candidate disability accommodations FAQs. We respond only to requests related to accessibility due to disability.
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Keywords: Disneyland Hong Kong, Hackensack , Lead Machine Learning Engineer - Personalization, Engineering , New York, New Jersey