Principal Machine Learning Engineer - Ad Intelligence

Job Description

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 Intelligence team is under Ad Platforms and its mission is to transform advertising and Disney's Ad platform with data and AI across TV and streaming video. 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 covering tech areas ranging from machine learning, big data, microservices to data visualization. Our team is seeking a principal research software developer 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, inquisitive, 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 machine learning statistics or analytics in a variety of areas to boost Hulu and Disney in every aspect of advertising, including inventory forecasting, planning, pricing, targeting, decisioning, and efficient ad delivery.
• Invent and iterate novel solutions to challenging ad related problems in fast turnaround.
• Lead the ads algorithm architecture design and iteration of the advertising system.
• Develop scalable and efficient methods for large scale data analysis and model development.
• Build and experiment brand new algorithms and models e2e throughout production rollout and continuous optimization.
• Collaborate with engineering teams, program managers, and product managers in an open, and creative environment.
• Mentor team members and guide their technical development.

WHAT TO BRING
• BS in computer science or equivalent
• At least 10 years of working experience on large scale machine learning, and statistics in leading internet companies. Experience in the advertising domain is preferred.
• Solid understanding on ML technologies, mathematics and statistics.
• Proficient with Java, Python, Scala, large scale ML/DL platforms and processing tech stack.
• Passion to understand the ad business and apply accurate research study according to the business scenario, and seek innovation opportunities to enhance business effectiveness
• Passion for technology, open to interdisciplinary work, and experience in building data-driven services and applications.
• Proven track record of thriving in a fast-paced, data-driven, collaborative and iterative applied research environment is required.

NICE-TO-HAVES
• MS or PhD(Preferred) in computer science or equivalent experience
• Experience in digital video advertising or digital marketing domain
• Experience with CTR/CVR model, generative AI
• Experience with feature store, audience segmentation and MLOps
• Experience with Tensorflow, Kubeflow or Sagemaker

The hiring range for this position in California is $180,646 to $265,430 per year and in Washington is $189,256 to $253,880 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.

This position is with Hulu, LLC, which is part of a business we call Shared Services.

Jobcode: Reference SBJ-gky7o8-44-212-94-18-42 in your application.