Jobs · Marketing · New Jersey

VP, Product AI/ ML

CoreWeave · Livingston, NJ · 3 wk ago
Marketing$233k–$341k/yrFull-time

The Role

You will lead the product strategy of our Research Training Stack, focusing on the specialized orchestration, evaluation, and iteration tools required for massive-scale pre-training and post-training. This is a mission-critical role at the intersection of high-performance computing (HPC) and cloud-native agility.

Core Responsibilities

  • Frontier Orchestration: Oversee the evolution of SUNK (Slurm on Kubernetes) to provide researchers with deterministic, bare-metal performance through a cloud-native interface.

  • Holistic Training Services: Beyond Slurm, drive the development of next-generation orchestrators and automated training-based evaluation frameworks that ensure model quality throughout the lifecycle.

  • Post-Training Excellence: Build the infrastructure required for sophisticated Reinforcement Learning (RL) and RLHF pipelines, enabling labs to refine foundation models with maximum efficiency.

  • Customer Advocacy: Act as the primary technical partner for lead researchers at global AI labs, translating their "future-state" requirements into actionable product roadmaps.

Requirements

  • Deep Research & Infrastructure Mastery: Proven leadership with at least 5+ years managing large-scale infrastructure at a top-tier research lab or an AI-native cloud provider. Domain Expertise: Deep, hands-on knowledge of Slurm, Kubernetes, and the specific networking requirements (InfiniBand/RDMA) for distributed training clusters.

  • Research Mindset: You likely come from a background supporting frontier model research (pre-training and post-training) and understand the "pain points" of a research scientist. Scaling Experience: A track record of delivering mission-critical services on multi-thousand GPU clusters (H100/Blackwell/Rubin architectures).

  • Strategic Vision: Ability to define "what's next" in the AI stack, from automated RL loops to specialized sandbox environments.

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