Principal Machine Learning Engineer

Disney Entertainment & ESPN Technology
On any given day at Disney Entertainment & ESPN Technology, we're reimagining ways to create magical viewing experiences for the world's most beloved stories while also transforming Disney's media business for the future. Whether that's evolving our streaming and digital products in new and immersive ways, powering worldwide advertising and distribution to maximize flexibility and efficiency, or delivering Disney's unmatched entertainment and sports content, every day is a moment to make a difference to partners and to hundreds of millions of people around the world.
A few reasons why we think you'd love working for Disney Entertainment & ESPN Technology

• Building the future of Disney's media business: DE&E Technologists are designing and building the infrastructure that will power Disney's media, advertising, and distribution businesses for years to come.
• Reach & Scale: The products and platforms this group builds and operates delight millions of consumers every minute of every day - from Disney+ and Hulu, to ABC News and Entertainment, to ESPN and ESPN+, and much more.
• Innovation: We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment & news.

Job Summary:
You will work on creating the best-in-class Recommendations & Discovery experiences for hundreds of millions of customers across Disney+, Hulu, ABC and ESPN. You will collaborate with Data Science/ML and Product teams to innovate on, develop and operate Recommendation Systems at scale.
This is an Individual Contributor leadership role in content recommendations. You will be expected to lead recommendation and personalization algorithm research, development, and optimization for our streaming app personalization across international regions we serve, and to coordinate requirements and manage stakeholder expectations with Product, Engineering, and Editorial teams. You will be expected to help meet KPIs for product areas and to set and meet deadlines for external. As an IC leader, you will also be responsible for helping to set the roadmap for algorithmic work - not only for how to approach product requests for new recommendation features, but for helping to drive larger company objectives in the areas of personalization and content recommendation.
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 Qualification:

• Track recordings of research & publications in recommendation system domain with deep neural net algorithms
• Strong proficiency in at least one of the following deep learning frameworks, tensorflow, pytorch
• Experiences 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

Preferred qualification:

• PhD in statistics, math, computer science, or related quantitative field
• Developing reporting dashboards such as Tableau or Looker
• Production experience with developing content recommendation algorithms at scale and familiar with metadata management, data lineage, and principles of data governance
• Deep understanding in personalization challenges in homepage experience and proven records of developing effective solutions

Experience with:

• 10+ years of analytical experience
• 8+ years of experience in developing highly scalable machine learning products
• 8+ years writing production-level, scalable Python codes

Required Education

• Master degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience

The hiring range for this position in San Francisco, CA is $222,200.00 - $297,900.00, in New York City, NY is $212,600.00 - $285,100.00 per year and in Seattle, WA is $212,600.00 - $285,100.00 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.