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With deep domain expertise, advanced technical capabilities, and a proven track record of successful collaborations, the AI Enablement & Machine Learning team at CNN is accelerating our digital transformation through strategic applications of machine learning and AI technologies.
The AI Systems group builds AI-powered applications and systems that solve real problems for CNN's audiences and internal teams.
Our work spans consumer-facing features (article summaries, weather summaries), internal AI tooling for editorial, product, design, engineering, and business teams, content and product classification systems, and the AI platform that powers it all — prompt management, evaluation, caching, versioning, deployment, and tenant management.
We are held to the high standards our audiences expect from a news organization: reliable, accurate, and trustworthy.
Your New Role... As a Software Engineer II on AI Systems, you will design, build, and operate AI-powered applications and the platform capabilities that support them. You will partner with ML engineers, editorial and product stakeholders, and platform engineers to ship features that improve CNN's user experience and internal productivity.
Key challenges you will tackle:LLM-Based Content Understanding: Build the in-house, LLM-based content understanding capability that replaces a vended classification product — improving quality, expanding adoption to new business domains across CNN, and powering downstream use cases including ad targeting, content routing, and brand safety.
Consumer-Facing AI Features: Ship and iterate on AI-powered features that reach millions of users — article summaries, weather summaries, and the next set of audience-facing experiences — with the accuracy and trustworthiness CNN's audiences expect.AI Platform Maturation: Grow CNN's AI platform capabilities — prompt management, evaluation, caching, versioning, deployment, and tenant management — so that AI features across CNN can be built, tested, and operated reliably and efficiently.
Internal AI Tooling: Build AI-assisted workflows for editorial, product, design, engineering, and business teams that drive measurable productivity gains.
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