Job Posting Title:
Sr ML EngineerReq ID:
10110883Job Description:
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.
Engineering Services designs, builds, and sustains technology that powers DE&E Technology’s worldwide content production and distribution platforms. In doing so, they contribute to a series of cross-functional services and technologies, including Quality Assurance, Data Analytics, Software Development, Broadcast Infrastructure, and Networking & Security.
Job Summary:
In this role you will focus on partnering with software services and engineering groups to lead and drive ML applications in those domains. You will conduct data exploration, analysis to motivate and drive ML usage across the engineering and services teams and provide ML consultancy. You will work on cross-functional products and push the envelope on data and ML focused solutions.
Responsibilities and Duties of the Role:
Drive data and ML driven solutions for diverse engineering use cases such as demand forecasting, capacity planning and management, or fraud and abuse prevention
Architect and build end to end ML models to drive data driven decisions
Be a ML thought partner to our stakeholders
Conduct data exploration, analysis and provide ML consultancy
Drive and maintain a culture of quality, innovation and experimentation
Work in an Agile environment that focuses on collaboration and teamwork
Required Education, Experience/Skills/Training:
Basic Qualifications
Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience
5+ years of equivalent data science experience, with 2+ years of relevant ML experience
Expertise in at least one of data science, machine (or deep) learning algorithms, and statistical methods to solve real-world engineering problems
Comfortable operating at all levels of the predictive stack and user behavior modeling including data collection, feature engineering, batch training and low-latency online serving
Strong mathematical skills with knowledge of statistical methods
Preferred Qualifications
MS or PhD in Computer Science or related fields
Familiarity with Python development ecosystem and technologies like Databricks, S3, Spark
Experience with graph-based data workflows such as Apache Airflow, Meson
Mentor colleagues on best practices and technical concepts of building large scale solutions
Job Posting Segment:
Product & Data EngineeringJob Posting Primary Business:
PDE - Engagement Experiences & PlatformsPrimary Job Posting Category:
Machine LearningEmployment Type:
Full timePrimary City, State, Region, Postal Code:
New York, NY, USAAlternate City, State, Region, Postal Code:
USA - CA - 1200 Grand Central Ave, USA - CA - 2450 Broadway, USA - CA - Market St, USA - WA - 925 4th AveDate Posted:
2025-01-240 applies
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