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Technical Program Manager - Performance & Benchmarking

CoreWeave
New York City, United Statesfull_timeVerifiedPosted 29 Jun 2026
πŸ’° $237,000/yr($177,000/yr – $237,000/yr)

About the role

CoreWeave is The Essential Cloud for AIβ„’. 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 atΒ www.coreweave.com.

What You'll Do:

The AI/ML TPM team owns delivery and execution across CoreWeave's AI/ML Platform Services organization. The team partners closely with Product, Engineering, Research, Infrastructure, and Go-to-Market teams to deliver scalable, reliable, and high-performance platforms that support the full AI lifecycle. AI/ML TPMs drive alignment and execution across highly technical, cross-functional teams to ensure the successful delivery of customer-facing infrastructure and platform capabilities used by researchers, engineers, and enterprise customers.

As a Technical Program Manager, you will lead complex, cross-functional programs across Performance & Benchmarking within our AI/ML Platform Services organization. This team is responsible for ensuring CoreWeave's infrastructure is performant, stable, and validated for demanding AI workloads before and as it reaches customers. The work spans infrastructure verification, benchmarking, observability, and performance readiness across new hardware platforms, clusters, and model workloads. You will partner with engineering, infrastructure, product, capacity, and go-to-market teams to drive programs that improve workload performance, validate new environments, operationalize benchmarking frameworks, and create visibility into how CoreWeave systems perform across models, hardware generations, and deployment contexts.

In this role, you will:

  • Drive end-to-end program execution for performance and benchmarking initiatives spanning infrastructure validation, performance testing, benchmark execution, observability, and launch readiness
  • Partner with engineering and infrastructure teams to deliver programs that verify new hardware platforms, clusters, and software environments meet CoreWeave standards for performance and stability
  • Lead cross-functional efforts to operationalize benchmarking frameworks that measure model performance, runtime efficiency, GPU utilization, and workload reliability across environments
  • Coordinate dependencies across platform engineering, infrastructure, capacity, product, and go-to-market teams to ensure performance findings are translated into roadmap priorities, customer readiness, and external proof points
  • Build program mechanisms for release readiness, benchmark planning, risk management, issue escalation, and post-launch review for performance-sensitive infrastructure initiatives
  • Establish dashboards, operating cadences, and success metrics to improve performance visibility, infrastructure validation coverage, benchmark repeatability, and time-to-readiness for new platforms
  • Help drive prioritization across performance bottlenecks, test gaps, and benchmark requests by aligning stakeholders on goals, tradeoffs, and measurable outcomes
  • Create clarity across ambiguous technical programs by aligning teams around performance goals, validation criteria, and execution milestones

Who You Are:

  • Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
  • 5+ years of technical program management experience in cloud infrastructure, distributed systems, high-performance computing, or AI/ML platforms
  • Experience leading large-scale cross-functional programs involving performance engineering, benchmarking, validation systems, or infrastructure readiness
  • Strong technical fluency in distributed systems, GPU or accelerator-based infrastructure, workload performance measurement, and large-scale infrastructure operations
  • Demonstrated ability to define program metrics and drive measurable outcomes in performance, reliability, scale, or operational maturity
  • Excellent communication skills, with experience influencing engineering, product, and infrastructure stakeholders
  • Experience with AI/ML benchmarking, performance analysis, or infrastructure validation for training and inference workloads
  • Familiarity with GPU cluster architecture, workload observability, hardware bring-up, a

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Company

CoreWeave

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