Senior Manager, Software Engineering, Machine Learning

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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 Machine Learning group within this team develops, deploys, and optimizes ML models that drive measurable business impact through better engagement and growth. The team owns two work streams — Engagement ML, which powers personalized recommendations, content reranking, and search for CNN's news audiences, and Growth ML, which drives revenue and user value through product recommendations, advertising optimization, and commercial experiences. The team uses rigorous experimentation to prove value and inform product strategy across all initiatives.

Our vision is that CNN's ML models drive measurable business impact through better engagement and growth, with rigorous experimentation that proves value and informs product strategy.

The Machine Learning group is composed of two work streams — Engagement ML and Growth ML. Engagement ML builds models that increase user engagement through personalized recommendations, intelligent page layouts, and content discovery. Growth ML builds models that drive business growth through product recommendations, advertising optimization, and conversion-focused experiences.

As the Senior Engineering Manager for Machine Learning, you will oversee both work streams, managing an Engineering Manager for Engagement ML and hiring an Engineering Manager for Growth ML, with a combined team growing to approximately 12 engineers through 2026. You will partner with the organization's Senior Technical Program Manager for cross‑team coordination and delivery.

Key challenges the team will tackle:

• Homepage Personalization:
  Launch personalization features on the web and app homepage that measurably improve engagement metrics
• Content Reranking:
  Deliver content and container reranking to production with demonstrated impact on user engagement
• All Access:
  Power search and recommendations for the All Access subscriber experience
• Editorial Signal Integration:
  Incorporate editorial signals (trending, breaking news, quality indicators) into ML models while maintaining editorial integrity

• AI‑Powered Commerce:
  Launch new AI‑powered experiences in partnership with the Underscored team
• Unified Page Layout Optimization:
  Establish a partnership with the ads team to balance ad revenue and content engagement through a single ML‑driven system
• Ad Modeling:
  Support DART on ad modeling initiatives to improve targeting, yield, and revenue optimization

• Support, coach, mentor, and provide valuable feedback to the individuals you manage to help them excel — across a range of roles including machine learning engineers, software engineers, and engineering managers as the team grows
• Manage and develop the Engagement ML Engineering Manager and hire and onboard a Growth ML Engineering Manager, building a strong leadership bench
• Work with…