Global GPU Capacity Lead (Kubernetes & Multi-Cloud)

Baseten; San Francisco (CA); On-site; USD 170,000 - 230,000; Full time

Benefits offered by this job

Competitive equity

100% medical/dental/vision coverage

Flexible PTO incl. Winter Break

Job summary

Baseten is seeking a Global Capacity Lead to architect, secure, and optimize our global GPU fleet that powers customers' AI workloads. You will own end-to-end capacity management, from securing multi-million dollar clusters to building automation ensuring 99.9% uptime across multi-cloud environments.

This is a high-stakes, hands-on engineering role combining Kubernetes expertise with strategic leadership. You will coordinate with SRE, Infra, and frontend teams, drive scalable capacity solutions,

Qualifications

• Bachelor's, Master's or Ph.D. in Computer Science, Engineering, Mathematics, or a related field.
• 5+ years of professional work experience in a high-growth environment, preferably at a hyperscaler or GPU provider.
• Deep expertise in Kubernetes, including taints, cordons, node draining, and custom operators.
• Demonstrated production experience with Go or Python and strong financial literacy for capacity modeling.
• High tenacity and collaborative mindset.

Responsibilities

• Lead Specialized Pods: manage full lifecycle of GPU pods (e.g., H100, B200) and assets.
• Advanced Orchestration: perform complex migrations and regional deployment constraints.
• Build for Scalability: design next-gen capacity management to handle 10x GPU volume.
• Financial Modeling: develop ROI models for GPU spend to sustain profitability.
• Cross-Team Collaboration: partner with SRE, Infra, and FDE teams on operations.
• Incident Response: lead capacity-crunch response and rapid workload re-coordination.

Skills

Kubernetes

Go or Python

Financial modeling

Collaborative mindset

Education

Bachelor's/Master's/PhD in CS/Engineering

Job description

Baseten is seeking a Global Capacity Lead to architect, secure, and optimize our global GPU fleet that powers customers' AI workloads. You will own end-to-end capacity management, from securing multi-million dollar clusters to building automation ensuring 99.9% uptime across multi-cloud environments.

This is a high-stakes, hands-on engineering role combining Kubernetes expertise with strategic leadership. You will coordinate with SRE, Infra, and frontend teams, drive scalable capacity solutions,