Senior Product Marketing Manager, AI Training Infrastructure

About this role

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com .

What You'll Do:

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.

About the role:

Positioning and messaging

• Own the AI Training Infrastructure narrative for CoreWeave. That narrative is built on real credibility: CoreWeave infrastructure has been used to train many of the most widely used models in production today. Your job is to deepen and expand that story, building the strategic positioning framework that ties CoreWeave Kubernetes Service, SUNK, and SUNK Anywhere into a coherent market story, deciding how each product is positioned relative to the others, and ensuring that framework holds across every customer-facing surface.

• Shape how CoreWeave competes in training-focused sales situations. That means owning the competitive positioning framework field teams use against alternative infrastructure approaches, the persona-specific messaging that translates infrastructure capabilities into outcomes research leaders and platform teams care about, and the launch narrative for new capabilities as they reach the market.

Customer proof

• Own the customer evidence strategy for AI Training Infrastructure. Decide which proof points matter for which buyers at which stage. Build the feedback loops that surface deployment insight from Solutions Architects and customer-facing engineers. Ensure that evidence reaches assets without losing specificity in translation. The goal is a proof strategy that makes every customer-facing asset more credible, not a library of case studies.

GTM and sales enablement

• Define how CoreWeave's training stack goes to market. Own the enablement framework for Sales and Solutions Architects. Set the competitive positioning strategy the field uses in training-focused deals. Partner with DevRel on content and enablement for technical audiences, including developers, researchers, and community contributors. That boundary requires active coordination and will evolve as both roles do. Partner with CoreWeave's technical and applied ML teams on benchmarking and performance validation that supports how the training stack is positioned and evaluated in market.

Metrics and measurement

• Define how product marketing's impact is measured for AI Training Infrastructure, not just whether assets were delivered. Own the metrics that matter: deal velocity, contract value, competitive win rates in training-related opportunities, and platform adoption and retention. Use that data to make the case internally for where AI Training Infrastructure messaging is moving deals and where it needs to change.

Who You Are:

• 5+ years in product marketing, technical marketing, or GTM, in cloud infrastructure, AI/ML, or developer tooling.

• Working fluency with Kubernetes. You do not need to have operated clusters, but you need to understand how teams use them and why the infrastructure decisions around them matter.

• Direct experience with or proximity to AI researchers: how they think, what they evaluate, what earns trust versus eye-rolls.

• Familiarity with the AI model development lifecycle from pre-training through fine-tuning, RL, and optimization. You know what this stage of the workflow costs teams when it breaks down.

• Demonstrated ability to build positioning and messaging for complex technical products that moved something, adoption, market perception, or competitive win rate. Not just produced, shipped.

• Sound judgment inside ambiguity. You have worked in a fast-moving org where role definitions shifted and used that as information, not a blocker.

Preferred:

• Experienc

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