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
Ad Platforms organization within Disney Entertainment and ESPN Technology is fully responsible for building, enhancing and maintaining the high-performance, distributed, microservice-based Advertising Platform across all of Disney online properties, including Hulu and ESPN+. We build and maintain proprietary technology, ranging from ad serving and ad delivery, campaign management, reporting as well as all the integrations internal and external that come with evolving and maintaining a best-in-class video advertising business.
The Ad Platform research team is under Ad Platforms and its mission is to transform advertising and Disney's Ad platform with AI and data science. We build solutions to measure and optimize every aspect of the advertising life cycle. Our tenant is a strong cross-domain team to deliver E2E solutions for machine learning and data science. Our team is seeking a lead machine learning engineer who will be an outstanding addition and leading development for prediction or optimization engines for addressable ad platforms. The right person for this role should be experienced in crafting implementation for either machine learning technologies or data-driven algorithms. If you are someone who is proactive and innovative in these domains, this is a phenomenal role for you!
WHAT YOU'LL DO
Drive ground-breaking innovation and apply state of the art AI and machine learning in a variety of areas to enhance every aspect of advertising, including inventory forecasting, ad experience, ad pacing, pricing, targeting, and efficient ad delivery.
Invent and iterate novel solutions for complex ad challenges with fast turnaround.
Lead the ad algorithm architecture design and iteration of the advertising system.
Develop scalable and efficient approaches for large scale data analysis and model development.
Build and experiment new algorithms and models end-to-end, from production rollout to continuous optimization.
Collaborate with engineering teams, product managers, and program managers in an open and creative environment.
Mentor team members and support their technical growth.
Minimum Qualifications:
Bachelors Degree in computer science or related field of study
7+ years of relevant engineering experience working experience at leading technology companies.
Strong knowledge of and experience implementing AI/ML technologies, mathematics and statistics.
Ability to collaborate with and lead projects across cross-functional teams such as Product Management, Architecture, and other Engineering teams
Proficient in Java, Python, Scala, large scale ML/DL platforms and processing tech stack.
Passionate about understanding the ad business, applying advanced research to relevant business scenarios, and seeking innovation opportunities to enhance business effectiveness.
Passionate about technology, open to interdisciplinary collaborations, and experienced in building data-driven services and applications.
A proven track record of thriving in a fast-paced, data-driven, and collaborative work environment is required.
NICE-TO-HAVES
MS or PhD(preferred) in computer science or equivalent experience
Experience in the advertising domain is preferred.
Experience in large scale machine learning.
Experience in LLM and GenAI.
Experience with forecasting algorithm is preferred.
Experience in digital video advertising or digital marketing domain
Experience with CTR/CVR model, generative AI, forecasting model.
Experience with feature store, audience segmentation and MLOps
Experience with Tensorflow, Kubeflow or Sagemaker
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