8 часов назад
Senior GPU Capacity and Optimization Planner (AI Infrastructure)
160 000 - 195 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior GPU Capacity and Optimization Planner (AI Infrastructure) (GPU capacity planning and cloud infrastructure): Managing and optimizing Crusoe Cloud’s high-performance GPU fleet with an accent on bin-packing, cluster utilization, and capacity allocation. Focus on translating commercial pipeline demand into datacenter hardware requirements, forecasting AI workload needs, and designing scalable scheduling and visualization tools.
Location: On-site in San Francisco, CA; Bellevue, WA; or Sunnyvale, CA, US
Salary: $160,000–$195,000 annually plus bonus and Restricted Stock Units
Company
is an AI infrastructure company operating vertically integrated systems from energy and physical infrastructure through cloud services, with a focus on sustainable computing.
What you will do
- Develop and execute GPU fleet bin-packing strategies to minimize fragmentation and maximize accelerated-compute cluster utilization.
- Partner with Sales, Customer Success, and Solutions Engineering to translate customer pipeline demand into datacenter hardware requirements.
- Coordinate with Fleet Management, Infrastructure Engineering, and Data Center Operations to support workload uptime and capacity execution.
- Build utilization models tracking GPU cluster headroom, workload density, and allocation velocity.
- Forecast demand based on commercial signals and large-scale AI training and inference trends to guide hardware placement and scheduling.
- Work with Core Software Engineering to automate allocation, scheduling, and visualization processes.
Requirements
- 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 such as AWS, GCP, Azure, or Oracle Cloud, or in a large-scale accelerated-compute cloud fabric.
- Foundational knowledge of GPU topologies, including NVIDIA H100 and B200 ecosystems.
- Ability to communicate infrastructure and physical-layout constraints to business stakeholders and translate commercial requirements for hardware engineering teams.
- Bachelor’s or Master’s degree in Computer Engineering, Computer Science, Operations Research, Industrial Engineering, Data Science, or an equivalent quantitative field.
- Technical familiarity with distributed AI training frameworks and multi-tenant cloud storage dynamics.
Nice to have
- Experience aligning large-scale computing infrastructure with environmental sustainability initiatives.
Culture & Benefits
- Competitive compensation, equity, and Restricted Stock Units.
- Paid time off, holidays, leave programs, parental leave, and volunteer time off.
- Health, dental, vision, life, disability, and mental health coverage, plus HSA contributions.
- Professional development, tuition reimbursement, commuter benefits, cell phone stipend, and daily meals allowance.
- 401(k) retirement plan with employer matching up to 4% of salary, plus global travel insurance and location-specific programs.
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