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Senior GPU Capacity Planner

Crusoe· Cloud Engineering
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San Francisco, CA - US, Sunnyvale, CA - US, Bellevue, WA - US$160k - $195k + equity + bonusFull-timePosted 3mo ago

About the role

Senior-level role focused on managing, optimizing, and forecasting Crusoe Cloud’s high-performance GPU fleet across multiple data centers. Cross-functional collaboration with Sales, Customer Success, Solutions Engineering, Fleet Management, and Infrastructure teams to maximize resource utilization, reduce fragmentation, and ensure seamless AI/ML performance while aligning compute with environmental sustainability.

Responsibilities

  • GPU Fleet Bin-Packing & Optimization: Develop and execute advanced bin-packing strategies to optimize GPU resource allocations within our data centers, minimizing fragmentation and maximizing cluster utilization.
  • GTM & Pipeline Alignment: Act as the primary technical capacity partner to Sales, Customer Success, and Solutions Engineering, reviewing upcoming pipeline demands and mapping them to physical hardware constraints.
  • Cross-Functional Capacity Execution: Collaborate tightly with Fleet Management, Infrastructure Engineering, and Data Center Operations to ensure maximum uptime of our customer workloads.
  • Utilization Modeling & Metrics: Design and implement models to track real-time GPU cluster headroom, workload densities, and allocation velocities to prevent supply bottlenecks.
  • Strategic Demand Forecasting: Synthesize commercial demand signals and large-scale AI training/inference architectural trends to inform hardware placement and scheduling.
  • Automation Requirements: Partner with Core Software Engineering to translate manual allocation processes into scalable, automated programmatic scheduling and visualization tools.

Qualifications

  • 3+ years of direct experience in Infrastructure Capacity Planning, Technical Product Management, or Systems Engineering with heavy exposure to machine-level resource scaling.
  • Experience working within a hyperscaler cloud environment (e.g., AWS, GCP, Azure, Oracle Cloud) or a specialized, large-scale AI/accelerated compute cloud fabric.
  • Solid foundational understanding of GPU topologies (e.g., NVIDIA H100/B200 ecosystems).
  • Proven ability to communicate complex infrastructure and physical layout constraints clearly to business stakeholders like Sales and Customer Success, while translating commercial requirements back to hardware engineers.
  • Bachelor’s or Master's degree in Computer Engineering, Computer Science, Operations Research, Industrial Engineering, Data Science, or an equivalent quantitative field.

Skills

Required:Capacity PlanningGPU Resource SchedulingCross-Functional CollaborationHyperscaler Experience
Nice to have:Data Modeling & Metrics

Benefits

  • Competitive compensation and equity packages
  • Restricted Stock Units
  • Paid time off, paid holidays & leave of absence programs
  • Comprehensive health, dental & vision insurance
  • Employer contributions to HSA account
  • Paid parental leave
  • Paid life insurance, short-term and long-term disability
  • Professional development & tuition reimbursement
  • Mental health & wellness support
  • Commuter benefits (parking & transit)
  • Cell phone stipend
  • 401(k) Retirement plan with company match up to 4% of salary
  • Volunteer time off
  • Global travel insurance & emergency assistance
  • Daily meals allowance
  • Additional perks & programs specific to location
Last updated Jul 22, 2026. Interested? Apply on the company site.

About Crusoe

The AI factory company | Renewable-powered AI infrastructure

Crusoe provides next-gen AI infrastructure and cloud compute using an energy-first approach. Deploy AI workloads at scale with reliable performance and 24/7 support.

AI infrastructureData centersEdge computingGPU computingRenewable energycloud computeenergy-first approachsetter-30
Company profileWebsite

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