Job Summary:
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:
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.
Basic Qualifications:
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 (., hypothesis testing, regression analysis)
Ability to articulate the usage and behavior of models and algorithms to both technical and non-technical audiences
Preferred Qualifications:
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 solutions
Experience with:
7+ years of experience in developing highly scalable machine learning products
7+ years writing production-level, scalable Python codes
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