Staff Machine Learning Engineer - Personalization

Spectrum - Seattle, WA

Full-time - Senior

Seattle, WA

Telecommunications

About the position

The Staff Machine Learning Engineer for Personalization at Warner Bros. Discovery will play a pivotal role in building and scaling the Direct-to-Consumer (DTC) personalization systems for the Max streaming app and future applications. This position requires a blend of technical leadership and collaboration with various teams to create a recommendation system that enhances user experience across multiple platforms. The role emphasizes innovation, rapid feature iteration, and the development of robust platforms and tools to support millions of users globally.

Responsibilities

• Architect, build and scale a recommendation system for Max, HBO, Discovery+, and other WBD offerings.
• Collaborate with ML/Ops engineers to enhance core components and infrastructure for model training, deployment, and serving.
• Drive ML projects from conception to completion in collaboration with data scientists, engineers, and product teams.
• Utilize and contribute to open-source cloud computing technologies.
• Support strategic planning and deliver against team goals with good judgment.
• Mentor and influence engineers across organizations, showcasing high-quality work.
• Foster a culture of experimentation and data-driven innovation, advocating for customer-centric solutions.

Requirements

• 8+ years of industry experience, with 4+ years in a tech lead role (preferred).
• Deep practical knowledge of large-scale recommender systems or ML ranking/retrieval/targeting systems.
• Knowledge of large-scale distributed application architecture and performance tuning.
• Good practical knowledge of the modern machine learning lifecycle.
• 5+ years of programming experience in Python/Java with rapid prototyping skills.
• Ability to drive the roadmap for scalable production-quality systems end-to-end.
• Excellent written and verbal communication skills, comfortable presenting to large audiences.
• Advanced degree (M.S. or Ph.D.) or equivalent industry experience in software engineering, computer science, machine learning, or related fields.
• Experience with cloud platforms such as AWS, GCP, or Azure.
• Familiarity with CI/CD tools like GitHub Actions and Jenkins.