Machine Learning Engineer II, CNN Digital Products and Services

Welcome to Warner Bros. Discovery… the stuff dreams are made of.

Who We Are…

When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next…

From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.

We are CNN. THE WORLD'S MOST ESSENTIAL AND ENGAGING SOURCE OF DIGITAL NEWS.

We are in the midst of rapid transformation and need our next generation of innovators, makers, and dreamers who will lead and drive our growth. We aim to make the world a better, more connected place.

About CNN Digital

CNN Digital is a global leader in news and information, reaching millions of users daily across web, mobile, and connected TV platforms. Our ML/AI team works at the intersection of journalism, technology, and user experience, building systems that help people discover and engage with the news that matters to them.

Your New Role…

CNN is seeking a Machine Learning Engineer II to build and deploy ML systems that power personalization, search, recommendations, and content understanding for millions of users across CNN's digital platforms. You will work on production ML systems with measurable product impact, collaborating with cross-functional teams of engineers, data scientists, product managers, and editorial staff.

Your Role Accountabilities…

• Build and deploy full-lifecycle machine learning systems in Python for CNN digital products, including personalization, search, recommendations, and content understanding
• Develop and maintain production ML pipelines, including feature engineering, model training, evaluation, and serving infrastructure
• Implement rigorous experimentation and A/B testing frameworks to validate model performance and product impact
• Optimize ML systems for real-time, web-scale performance serving millions of users
• Partner with platform and infrastructure teams to ensure ML systems meet reliability, scalability, and performance standards
• Contribute to code reviews, documentation, and team knowledge sharing

Qualifications & Experience…

Required Qualifications:

• Graduate degree (MS or PhD) in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field
• 2+ years of professional experience building and deploying machine learning systems in production environments
• Strong Python programming skills and experience with machine learning frameworks (e.g., scikit-learn or similar)
• Experience across the full ML lifecycle, including data preprocessing, feature engineering, model training, evaluation, and deployment
• Solid understanding of software engineering best practices, including version control, testing, and CI/CD
• Ability to collaborate effectively with cross-functional partners
• Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders

Preferred Experience:

• Experience working on large-scale consumer internet products (e.g., social, streaming, e-commerce, media)
• Hands-on experience with recommendation systems, search, NLP, or information retrieval
• Familiarity with data pipelines, feature stores, or embedding infrastructure
• Experience with experimentation platforms, A/B testing, and experimentation analysis
• Knowledge of cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes)
• Interest in generative AI applications and/or the media and news industry

Technical Skills:

• Languages: Python (required), SQL
• ML Frameworks: scikit-learn or similar
• Tools: Git, MLflow or similar MLOps tools
• Data: Experience working with large datasets, distributed processing, and feature engineering
• Deployment: REST APIs, model serving, monitoring, and observability

How We Get Things Done…

This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview.

Championing Inclusion at WBD

Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation