Principal AI/ML Engineer - AdTech
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About the Role
WHO WE ARE
Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.
Role Description
As a Principal AI/ML Engineer in our AdTech team, you will be a key individual contributor driving the development of advanced machine learning models and AI-driven features for our advertising platform. You will design, build, and deploy ML solutions for campaign optimization, user personalization, and creative content generation, operating at large scale and low latency to handle billions of ad events per day. This role requires deep expertise in machine learning techniques and the programmatic advertising ecosystem (e.g., real-time bidding and digital marketing data). You will work closely with engineering, product, and data science teams to ensure our ML systems are highly performant, scalable, and reliable. You will also spearhead innovation by leveraging large language models (LLMs) and intelligent agent architectures to create new capabilities that automate and enhance advertising campaigns.
Key Responsibilities
- Machine Learning Leadership: Lead the design and implementation of scalable, high-performance, and resilient ML solutions for AdTech use cases. You will set technical direction for integrating AI/ML into our Demand-Side Platform and broader ad tech stack.
- ML System Design: Architect and evolve the end-to-end machine learning pipeline – from data ingestion and training to real-time inference, for our real-time bidding, targeting, and optimization algorithms. Ensure that models seamlessly integrate with our ad serving architecture and handle low-latency, high-throughput requirements.
- Technical Strategy: Define the technical roadmap and vision for AI/ML in our platform, evaluating new tools and techniques (including the latest in deep learning and LLMs) and making strategic build-vs-buy decisions. Continuously assess emerging technologies to keep our AdTech capabilities on the cutting edge. &l
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