# Senior GPU Capacity Planner

**Company:** [Crusoe](https://hotfix.jobs/companies/crusoe)
**Location:** San Francisco, CA, Sunnyvale, CA, Seattle, WA
**Role:** Business Operations
**Salary:** $160k – $195k/yr
**Experience:** 3+ years
**Skills:** Infrastructure Capacity Planning, Gpu Resource Management, Bin-Packing Optimization, Nvidia Gpu Topologies, Systems Engineering, Technical Product Management, Cross-Functional Collaboration, Demand Forecasting, Utilization Modeling
**Posted:** 2026-06-25

> Own day-to-day management, allocation, and bin-packing optimization of Crusoe Cloud's GPU fleet. Bridge technical infrastructure with GTM teams to maximize utilization and align commercial demand with datacenter capacity.

## Job Description

## What You'll Be Working On

**GPU Fleet Bin-Packing & Optimization**
- Develop and execute advanced bin-packing strategies to optimize GPU resource allocations within data centers
- Minimize fragmentation and maximize cluster utilization

**GTM & Pipeline Alignment**
- Act as the primary technical capacity partner to Sales, Customer Success, and Solutions Engineering
- Review upcoming pipeline demands and map them to physical hardware constraints

**Cross-Functional Capacity Execution**
- Collaborate tightly with Fleet Management, Infrastructure Engineering, and Data Center Operations
- Ensure maximum uptime of customer workloads

**Utilization Modeling & Metrics**
- Design and implement models to track real-time GPU cluster headroom, workload densities, and allocation velocities
- Prevent supply bottlenecks

**Strategic Demand Forecasting**
- Synthesize commercial demand signals and large-scale AI training/inference architectural trends
- 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

## What You'll Bring to the Team

- 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
- Translate 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

## Bonus Points

- Deep technical familiarity with distributed AI training frameworks and multi-tenant cloud storage dynamics
- Passion for green energy and aligning massive computing scales with environmental sustainability initiatives

## 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

**Compensation Range:** $160,000 - $195,000 + Bonus. Restricted Stock Units are included in all offers.

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