Senior GPU Capacity Planner
Crusoe · San Francisco, CA - US ·
- Work mode
- Onsite
- Seniority
- Senior
- Experience
- 3+ years
- Salary
- USD 160,000 – 195,000 / year
Crusoe · San Francisco, CA - US ·
Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.
We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.
We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.
If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.
At Crusoe, the Capacity Planning & Efficiency team operates at the critical intersection of all Crusoe products, services, and underlying physical infrastructure. As the Senior GPU Capacity and Optimization Planner, you will own the day-to-day management, allocation, and strategic bin-packing optimization of Crusoe Cloud’s high-performance GPU fleet. This is a highly cross-functional, high-impact role that bridges the gap between our technical infrastructure and our Go-To-Market (GTM) engine.
You will work closely with Sales, Customer Success, Solutions Engineering, and Fleet Management to translate commercial customer pipelines into requirements within the datacenter. Your mission will be to maximize resource utilization, eliminate fragmentation across accelerated computing clusters, and ensure our AI/ML customers receive seamless performance, directly supporting Crusoe’s mission to align the future of computing with environmental sustainability.
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.
Proven Capacity & Scheduling Domain Expertise: 3+ years of direct experience in Infrastructure Capacity Planning, Technical Product Management, or Systems Engineering with heavy exposure to machine-level resource scaling.
Hyperscaler Experience: Experience working within a hyperscaler cloud environment (e.g., AWS, GCP, Azure, Oracle Cloud) or a specialized, large-scale AI/accelerated compute cloud fabric.
GPU & Accelerated Compute Knowledge: Solid foundational understanding of GPU topologies (e.g., NVIDIA H100/B200 ecosystems).
Strong Cross-Functional Navigation: 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.
Education: Bachelor’s or Master's degree in Computer Engineering, Computer Science, Operations Research, Industrial Engineering, Data Science, or an equivalent quantitative field.
Deep technical familiarity with distributed AI training frameworks and multi-tenant cloud storage dynamics.
A 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
Compensation will be paid in the range of up to $160,000 - $195,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data.
Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.