AI/ML Platform TPM: Performance & Benchmarking Lead

CoreWeave; San Francisco (CA); On-site; USD 177,000 - 237,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) with employer match

Flexible PTO

Equity awards

Tuition Reimbursement

ESPP

Parental Leave

On-site lunch

Job summary

CoreWeave, The Essential Cloud for AI, seeks a Technical Program Manager to lead end-to-end performance and benchmarking programs within the AI/ML Platform Services group. You will partner with engineering, infrastructure, product, and GTM teams to drive validation, benchmarking, and readiness for new hardware and software environments.

You will own metrics, dashboards, and launch readiness processes, translating performance findings into roadmap priorities and customer-ready capabilities across

Qualifications

• 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, and performance bottleneck analysis.
• Understanding of benchmarking methodologies, reproducibility, test coverage, and tradeoffs between performance, stability, utilization, and customer readiness.

Responsibilities

• 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.

Skills

Technical program management

Cloud infrastructure

Distributed systems

Performance benchmarking

GPU/accelerator infra

Cross-functional leadership

Education

Bachelor's degree in CS/Engineering or equivalent

Job description

CoreWeave, The Essential Cloud for AI, seeks a Technical Program Manager to lead end-to-end performance and benchmarking programs within the AI/ML Platform Services group. You will partner with engineering, infrastructure, product, and GTM teams to drive validation, benchmarking, and readiness for new hardware and software environments.

You will own metrics, dashboards, and launch readiness processes, translating performance findings into roadmap priorities and customer-ready capabilities across