Senior Product Marketing Manager, AI Training Infrastructure

CoreWeave•Sunnyvale, CA

4d•$177,000 - $237,000•Onsite

About The Position

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.

Requirements

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.

Nice To Haves

Experience marketing platform or infrastructure products where the buyer is a platform engineer, research lead, or technical architect.
Familiarity with schedulers, clusters, or distributed training workloads, Slurm, Kubernetes-native training, or both.
Track record across multiple products or a portfolio simultaneously, not a single-product PMM motion.
Background in developer tools, HPC, or AI infrastructure. You have marketed highly technical products to audiences who evaluate claims on technical merit, not positioning.

Responsibilities

Own the AI Training Infrastructure narrative for CoreWeave.
Build the strategic positioning framework that ties CoreWeave Kubernetes Service, SUNK, and SUNK Anywhere into a coherent market story.
Shape how CoreWeave competes in training-focused sales situations.
Own the customer evidence strategy for AI Training Infrastructure.
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.
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.
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.