Principal Machine Learning Engineer

Disney Entertainment & ESPN TechnologyNew York, NY
434d$202,900 - $272,100

About The Position

The position involves leading the development and optimization of recommendation systems for Disney's streaming services, including Disney+, Hulu, ABC, and ESPN. The role focuses on creating best-in-class recommendations and discovery experiences for millions of customers, collaborating with various teams to innovate and enhance personalization algorithms. As an individual contributor leader, the candidate will set the roadmap for algorithmic work and help meet key performance indicators (KPIs) for product areas.

Requirements

  • In-depth understanding of deep learning technology in recommendation systems or NLP fields.
  • Proficiency in at least one deep learning framework (TensorFlow, PyTorch).
  • Experience building and deploying full stack ML pipelines including data extraction, model training, and deployment.
  • Track record of deploying and maintaining pipelines using AWS, Docker, and Airflow.
  • Experience engineering big-data solutions using Databricks, S3, and Spark.
  • Understanding of statistical concepts such as hypothesis testing and regression analysis.
  • Ability to articulate model usage and behavior to technical and non-technical audiences.

Nice To Haves

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

Responsibilities

  • Lead recommendation and personalization algorithm research, development, and optimization.
  • Collaborate with Data Science/ML and Product teams to innovate on recommendation systems.
  • Coordinate requirements and manage stakeholder expectations with Product, Engineering, and Editorial teams.
  • Help meet KPIs for product areas and set deadlines for tools like offline evaluation tools for algorithms.
  • Set the roadmap for algorithmic work and drive larger company objectives in personalization and content recommendation.

Benefits

  • Medical benefits
  • Financial benefits
  • Bonus and/or long-term incentive units based on position and level.
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