Warner Bros. Discovery is looking to build and scale the personalization and search platforms for the global streaming app Max, as well as ongoing and future streaming initiatives, to serve over 100 million users worldwide.
Requirements
- Familiarity with the practical aspects of machine learning is required.
- Proficient in both Python and OOP languages including GoLang, Java or C++.
- Experience in deploying complex and large scale machine learning algorithms and advanced modeling solutions.
- Experience with recommender/search/ad serving algorithms and systems is a plus.
Responsibilities
- Architect and develop robust engineering solutions that utilize machine learning models and algorithms to support personalization's.
- Build and lead a world-class team of machine learning and full stack engineers.
- Be a hands-on leader and mentor the team in the latest machine learning technologies and processes.
- Partner closely with platform and infra teams to build robust fault tolerant solutions and accelerate the learning cycle.
- Partner closely with downstream application teams to develop a flexible and resilient interface between ML products and downstream applications.
- Partner closely with the ML Platform team to build flexible and resilient interfaces for training, serving and feature needs for personalization products.
- Develop and evangelize engineering best practices for scoping, building, validating, deploying, and monitoring ML/AI products.
Other
- Manage project priorities and ensure timely delivery.
- Partner closely with business and data science leadership for opportunity sizing and prioritizing product capabilities.
- Develop ML Systems roadmap in partnership with Data Science teams, and educate both internal and external stakeholders at all levels to drive resourcing and implementation.
- Self-starter and self-motivated with the proven ability to deliver results in a fast-paced, high-energy environment.
- Strong communication skills and the ability to explain complex engineering systems to non-technical audience.
