Machine Learning Engineer II, CNN Digital Products and Services

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 bringing our characters to life, the bringing them to your living rooms and the 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 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.

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.

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.

• 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

• 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

• 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

• 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

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.…