Technical Program Manager, CoreWeave

• This role is ideal for someone who thrives at the intersection of distributed systems and AI infrastructure, has deep technical fluency in workload orchestration or scheduling, and excels at building the operational structure and visibility required to scale complex, high-throughput systems
• Bachelor’s degree in a technical field or equivalent experience
• 8+ years of technical program management experience in distributed systems, cloud infrastructure, or ML/AI platforms
• Proven success leading programs involving large-scale orchestration or scheduling systems (e.g., Kubernetes, Ray, Slurm, Kueue, or proprietary systems)
• Strong technical fluency in distributed computing, job scheduling, Kubernetes orchestration, and benchmarking methodologies
• Demonstrated ability to define success metrics and drive measurable improvements in performance, reliability, or efficiency
• Exceptional communication and collaboration skills, with a track record of aligning multiple teams and stakeholders on complex technical initiatives
• This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency

Desirable

• CoreWeave’s AI/ML Platform Services organization is responsible for the orchestration layer that schedules and manages AI workloads across CoreWeave’s GPU-accelerated infrastructure
• As a Technical Program Manager focused on orchestration and model benchmarking, you will drive programs that define how large-scale AI workloads are scheduled, executed, and evaluated for performance and cost efficiency
• You’ll partner with engineering, infrastructure, and product teams to evolve CoreWeave’s orchestration systems—including Slurm-on-Kubernetes (SUNK) and future orchestrators—while building robust benchmarking and observability frameworks that help customers and internal teams compare model performance, runtime efficiency, and GPU utilization across environments
• Drive end-to-end program management for cluster orchestration initiatives—spanning SUNK, Kubernetes, and emerging workload schedulers
• Lead cross-functional efforts to deliver next-generation cluster orchestration capabilities for distributed AI training and inference workloads
• Partner with engineering and product to define roadmaps for cluster utilization, scheduling efficiency, preemption logic, multi-tenant fairness, and workload resilience
• Own the execution of model benchmarking programs—establishing frameworks, datasets, and metrics to measure model performance, throughput, latency, and cost across hardware types and orchestration environments
• Develop and scale processes for cross-team dependency management, performance testing, and release management — owning external release management for SUNK and other cluster orchestrators, including planning, coordination, and rollout of customer-facing updates
• Collaborate with infrastructure and DevOps teams to ensure orchestration systems meet CoreWeave’s reliability and scalability goals
• Build program dashboards, success metrics, and feedback loops to improve workload scheduling efficiency, GPU and cluster utilization, and time-to-deployment
• Create strong communication channels between AI Platform Engineering, Infrastructure, and Product to align roadmap priorities and deliver predictable, high-impact outcomes