Lead Machine Learning Engineer, Personalization & Recommendations

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.
  

Our team is responsible for developing, implementing, and maintaining Hulu's recommendation and personalization algorithms. As part of this team, you will collaborate with Engineering, Product, and Data teams to apply machine learning techniques to achieve strategic personalization goals. This is an Individual Contributor role in content recommendations. You will be expected to lead recommendation and personalization algorithm research, development, implementation, and optimization for product areas, and to coordinate requirements and manage stakeholder expectations with Product, Engineering, and Editorial teams. As an IC, 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:

• 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.

Experience with:

• 7 years of experience in developing highly scalable machine learning products
• 7 years writing production-level, scalable Python codes

Basic qualification:

• 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:

• 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 in personalization challenges in homepage experience and proven records of developing effective solution

Required Education:

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

#DISNEYTECH

The hiring range for this position in New York, NY & Seattle, WA is $172,300-$231,100 per year, in San Francisco, CA is $180,200.00 to $241,600.00 per year and in Los Angeles, CA is $164,500.00 to $220,600.00 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.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.