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Principal Machine Learning Engineer

Job ID 10106487 Location San Francisco, California, United States / New York, New York, United States / Seattle, Washington, United States Business Disney Entertainment & ESPN Technology Date posted Dec. 04, 2024
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Job Summary:

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 and internally facing tools, such as offline evaluation tools for pre-production algorithms. 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:

  • Experience with algorithm and ML model implementation & operation at scale, for consumer facing experiences

  • Ability to deep dive into individual components & systems as well as understand overall framework/architecture

  • Passion for consumer facing experiences

  • Analytical, data driven and pragmatic approach

  • Excellent written and oral communication skills

  • Collaborative, self-starter

Required Education, Experience/Skills/Training:

  • In-depth understanding of deep learning technology in recommendation system or NLP fields

  • 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 of deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark

  • 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

  • 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 related analytical experience

  • 8+ years of experience in developing highly scalable machine learning products

  • 8+ 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

#DISNEYTECH


The hiring range for this position in Los Angeles, CA is $202,900 - $272,100 per year, in San Francisco, CA $222,200 - $297,900 and in New York & Seattle, WA is $212,600 - $285,100 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.

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About Disney Entertainment & ESPN Technology:

Disney Entertainment and ESPN Technology (DE&E Technology) provides the technological backbone and product development for Disney’s two media business units, while helping to keep the company at the vanguard of innovation – enabling the Company to continuously leverage technology to enhance storytelling and creativity, while delivering scalability, flexibility, and efficiency for its businesses.

About The Walt Disney Company:

The Walt Disney Company, together with its subsidiaries and affiliates, is a leading diversified international family entertainment and media enterprise that includes three core business segments: Disney Entertainment, ESPN, and Disney Experiences. From humble beginnings as a cartoon studio in the 1920s to its preeminent name in the entertainment industry today, Disney proudly continues its legacy of creating world-class stories and experiences for every member of the family. Disney’s stories, characters and experiences reach consumers and guests from every corner of the globe. With operations in more than 40 countries, our employees and cast members work together to create entertainment experiences that are both universally and locally cherished.

This position is with Disney Streaming Technology LLC, which is part of a business we call Disney Entertainment & ESPN Technology.

Disney Streaming Technology LLC is an equal opportunity employer. Applicants will receive consideration for employment without regard to race, religion, color, sex, sexual orientation, gender, gender identity, gender expression, national origin, ancestry, age, marital status, military or veteran status, medical condition, genetic information or disability, or any other basis prohibited by federal, state or local law. Disney champions a business environment where ideas and decisions from all people help us grow, innovate, create the best stories and be relevant in a constantly evolving world.

DISABILITY ACCOMMODATION FOR EMPLOYMENT APPLICATIONS

The Walt Disney Company and its Affiliated Companies are Equal Employment Opportunity employers and welcome all job seekers including individuals with disabilities and veterans with disabilities. If you have a disability and believe you need a reasonable accommodation in order to search for a job opening or apply for a position, email Candidate.Accommodations@Disney.com with your request. This email address is not for general employment inquiries or correspondence. We will only respond to those requests that are related to the accessibility of the online application system due to a disability.

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