Crusoe
Senior GPU Capacity Planner
$160K–$195K
San Francisco, CA - US +2 · On-site · Senior · Full-time · Posted Jun 25, 2026
- Location
- San Francisco, CA - US
Sunnyvale, CA - US
Bellevue, WA - US - Experience
- 3+ years; stated alternatives are Infrastructure Capacity Planning, Technical Product Management, or Systems Engineering.
- Education
- Bachelor’s or Master's degree in Computer Engineering, Computer Science, Operations Research, Industrial Engineering, Data Science, or an equivalent quantitative field.
About the job
Owns GPU fleet capacity planning and optimization, aligning customer demand with physical infrastructure to maximize utilization and support AI workloads.
What you'll do
- Optimize GPU allocations to reduce fragmentation and increase cluster utilization.
- Coordinate with commercial and infrastructure teams to align customer pipeline demands with available hardware.
- Model capacity and forecast demand; help define automation for allocation and scheduling.
What they ask for
- 3+ years of experience in infrastructure capacity planning, technical product management, or systems engineering involving machine-level resource scaling.
- Experience in a hyperscaler cloud environment or large-scale AI/accelerated compute cloud fabric.
- Foundational knowledge of GPU topologies, such as NVIDIA H100/B200 ecosystems.
- Bachelor’s or Master's degree in a specified quantitative field.
Nice to have
- Familiarity with distributed AI training frameworks and multi-tenant cloud storage dynamics.
- Interest in green energy and environmental sustainability.
Pay
Up to $160,000 - $195,000 USD base salary; bonus amount not specified
Tools
AWS, GCP, Azure, Oracle Cloud, NVIDIA H100/B200
AI focus
Plans and optimizes GPU capacity for AI/ML workloads, including demand forecasting for large-scale AI training and inference.
Model-written summary · the original posting is authoritative