Senior Product Marketing Manager, AI Training Infrastructure

As Senior Product Marketing Manager for AI Training Infrastructure, you will own CoreWeave's AI Training Infrastructure story, all aspects of building and training a model, and partner on all post-training and optimization launches and narratives.

The role is not organized around a product list. It is organized around what research and platform teams are actually trying to accomplish at this stage, and the infrastructure decisions that either let them move fast or slow them down. SUNK is the most differentiated expression of CoreWeave's answer to that problem, the product in this scope with the deepest operational proof at scale. The broader story spans CoreWeave Kubernetes Service and a growing Kubernetes-native training surface expanding independently of Slurm. That includes understanding where open source frameworks like Ray, SkyPilot, and Kueue fit in the conversation, where community debate is shaping buyer expectations, and how ecosystem partnerships factor into how teams evaluate and adopt training infrastructure.

You are not inheriting four separate product stories and stitching them together. You are building the connective narrative across CoreWeave's training stack and the broader ML ecosystem it connects to, including the experiment tracking workflows, open source tooling, and practitioner communities that researchers already operate in. CoreWeave's integration with Weights and Biases connects infrastructure signals to the experiment tracking tools researchers already use. Part of this role is understanding how that integration shapes researcher perception of CoreWeave and building messaging around it. That means translating capabilities across the stack, topology-aware scheduling, bare-metal performance, Kubernetes-native lifecycle management, automated cluster health management, into messaging that resonates with AI research leaders, platform teams, and the wider ML researcher community beyond the largest labs.

Positioning and messaging

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