The Walt Disney Company (France)
Senior Machine Learning Engineer
The Walt Disney Company (France), San Francisco, California, United States, 94199
Overview
Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally. The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world. Disney Entertainment & ESPN Product 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. We are seeking a Senior Machine Learning Engineer to contribute to the development and deployment of cutting-edge recommendation and personalization algorithms that power user experiences across Disney+, Hulu, ABC, and ESPN. As a member of our team, you will work closely with Product, Engineering, and Data teams to build intelligent systems that serve hundreds of millions of users worldwide. In this role, you will be responsible for designing, implementing, and optimizing machine learning models for content recommendation and user personalization. You’ll take ownership of key projects, contribute to technical design and experimentation, and help translate product needs into scalable ML solutions. This is a strong individual contributor role for engineers with a solid foundation in machine learning and a passion for applied work in large-scale, real-world environments. You will have opportunities to grow your technical influence, deepen your domain expertise, and help drive innovation across personalization surfaces. 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 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 (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 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
5+ years of experience in developing highly scalable machine learning products 5+ 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 The hiring range for this position in New York, NY & Seattle, WA is $145,400 to $195,000 per year, in Los Angeles/Santa Monica, CA is $138,900 to $186,200 per year and in San Francisco, CA is $152,100 to $203,900 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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Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally. The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world. Disney Entertainment & ESPN Product 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. We are seeking a Senior Machine Learning Engineer to contribute to the development and deployment of cutting-edge recommendation and personalization algorithms that power user experiences across Disney+, Hulu, ABC, and ESPN. As a member of our team, you will work closely with Product, Engineering, and Data teams to build intelligent systems that serve hundreds of millions of users worldwide. In this role, you will be responsible for designing, implementing, and optimizing machine learning models for content recommendation and user personalization. You’ll take ownership of key projects, contribute to technical design and experimentation, and help translate product needs into scalable ML solutions. This is a strong individual contributor role for engineers with a solid foundation in machine learning and a passion for applied work in large-scale, real-world environments. You will have opportunities to grow your technical influence, deepen your domain expertise, and help drive innovation across personalization surfaces. 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 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 (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 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
5+ years of experience in developing highly scalable machine learning products 5+ 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 The hiring range for this position in New York, NY & Seattle, WA is $145,400 to $195,000 per year, in Los Angeles/Santa Monica, CA is $138,900 to $186,200 per year and in San Francisco, CA is $152,100 to $203,900 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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