Senior GPU Capacity Planner
Crusoe is an AI infrastructure and cloud computing company. It provides GPU compute, AI model training and inference, developer tools, managed orchestration, data centers, and energy infrastructure for AI builders and enterprise customers.
Maintainer signals as of 8/23/2026
Funding history
Projects
About Crusoe, Inc
Crusoe designs, builds, and operates energy-first AI infrastructure, including high-performance data centers, modular AI factories, and Crusoe Cloud. Its cloud platform provides NVIDIA and AMD GPU compute, scalable storage, high-performance networking, managed Kubernetes and Slurm, observability, model training, fine-tuning, and inference services. Crusoe serves AI developers, startups, enterprises, and teams running production-scale AI workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Manage the allocation and optimization of a high-performance GPU fleet by aligning customer demand with physical hardware constraints, developing bin-packing and utilization models, forecasting demand, coordinating capacity execution across infrastructure and data center operations, and automating scheduling and visualization processes.
Requirements
- 3+ years of experience in infrastructure capacity planning, technical product management, or systems engineering.
- Experience with machine-level resource scaling.
- Experience in a hyperscaler cloud environment or large-scale accelerated compute cloud.
- Understanding of GPU topologies, including NVIDIA H100 and B200 ecosystems.
- Ability to communicate infrastructure constraints to business stakeholders.
- Bachelor’s or Master’s degree in Computer Engineering, Computer Science, Operations Research, Industrial Engineering, Data Science, or an equivalent quantitative field.
Responsibilities
- Develop and execute GPU bin-packing strategies.
- Align commercial pipeline demand with physical hardware constraints.
- Collaborate with fleet management, infrastructure engineering, and data center operations.
- Design models to track GPU cluster headroom, workload density, and allocation velocity.
- Forecast demand based on commercial signals and AI training and inference trends.
- Translate manual allocation processes into automated scheduling and visualization tools.
Benefits
- Competitive compensation and equity packages
- Restricted Stock Units
- Paid time off
- Paid holidays
- Leave of absence programs
- Comprehensive health insurance
- Dental insurance
- Vision insurance
- Employer contributions to HSA account
- Paid parental leave
- Paid life insurance
- Short-term disability insurance
- Long-term disability insurance
- Professional development
- Tuition reimbursement
- Mental health and wellness support
- Commuter benefits for parking and transit
- Cell phone stipend
- 401(k) retirement plan with company match up to 4% of salary
- Volunteer time off
- Global travel insurance and emergency assistance
- Daily meals allowance
- Location-specific perks and programs