This executive leader will own the product strategy and engineering execution for the Research Training Stack, focusing on the specialized orchestration, evaluation, and iteration tools required for massive-scale pre-training and post-training.

Key responsibilities include:

• 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: 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 include:

• Proven leadership experience in engineering leadership, with at least 5+ years managing large-scale infrastructure at a top-tier research lab or an AI-native cloud provider.

• Deep, hands-on knowledge of Slurm, Kubernetes, and the specific networking requirements (InfiniBand/RDMA) for distributed training clusters.

• Research mindset and understanding of the 'pain points' of a research scientist.

• Scaling experience delivering mission-critical services on multi-thousand GPU clusters (H100/Blackwell/Rubin architectures).

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

Why CoreWeave?

In 2026, CoreWeave is the foundation of the largest infrastructure buildout in human history. We are building AI Factories, not just data centers.

• Silicon-Up Innovation: Work directly with the latest NVIDIA architectures.

• Impact: You will be the architect of the environment that enables the next new discovery.

Velocity: We move at the speed of the researchers we support, bypassing legacy cloud bottlenecks to deliver raw power.

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