Senior Capacity Planner

DigitalOcean

$106K — $132K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in capacity planning or related analytical role
  • Strong understanding of GPU hardware market and performance characteristics
  • Familiarity with serverless inference workloads
  • Experience analyzing demand data for resource optimization
  • Proficient in SQL and data visualization tools like Looker or Grafana
  • Interest in building automation and tooling to enhance efficiency
  • Knowledge of data center rack and power planning concepts
  • Excellent communication skills for cross-functional collaboration

Responsibilities

  • Analyze serverless model usage to identify optimization opportunities
  • Implement GPU server allocation strategies for enhanced revenue
  • Develop tools to automate model-to-server assignment processes
  • Monitor GPU hardware market trends to guide procurement efforts
  • Track GPU infrastructure capacity across global data centers
  • Collaborate with multiple teams to plan GPU server deployments
  • Forecast future GPU demand to inform procurement timelines
  • Identify and optimize GPU hardware placement across infrastructure
  • Create dashboards for tracking GPU utilization and capacity trends

Benefits

  • Hybrid work model
  • Opportunities for career growth and development
  • Access to cutting-edge technology in cloud computing and AI
  • Collaboration with a dynamic team dedicated to innovation
  • Work in a company that values passion and dedication to problem-solving
Full Job Description
We are looking for a Senior Capacity Planner who is passionate about growing DigitalOcean's Serverless Instance offering through physical infrastructure optimization.

As a Senior Capacity Planner at DigitalOcean, you will join a dynamic team dedicated to revolutionizing cloud computing and AI. Reporting to the Capacity Planning Lead, you will drive utilization across our Serverless Instance offering by predicting customer demand shifts and following novel model releases. After establishing processes and automation, you will additionally focus on deploying new GPU hardware and working with cross functional stakeholders to optimize our physical infrastructure.
What You'll Do:
  • Analyze usage statistics across serverless inference models and spot demand to identify optimization opportunities in server assignment
  • Make and implement recommendations on GPU server allocation across models to maximize revenue and utilization
  • Build tools and processes to automate and streamline model-to-server assignment decisions, reducing manual analysis over time
  • Maintain a deep, current understanding of the GPU hardware market - new models, availability, price/performance tradeoffs - to inform procurement and deployment decisions
  • Track rack and power capacity for GPU infrastructure across global data centers
  • Partner with DCOPS, Network Engineering, Product, and Delivery teams to plan and execute physical GPU server deployments
  • Forecast future GPU demand (both inference spot capacity and physical infrastructure) to inform procurement timelines
  • Identify opportunities to redistribute or optimize existing GPU hardware placement across racks and cabinets
  • Build dashboards and reporting to track GPU utilization, spot capacity trends, and deployment status
  • Escalate capacity risks or bottlenecks before they impact GPU availability or revenue
Key Metrics:
  • Revenue impact from optimized serverless inference server assignment
  • Serverless inference spot capacity utilization
  • Forecast accuracy for physical GPU infrastructure needs
  • On-time delivery of GPU hardware deployments
  • Rack/power capacity utilization for GPU fleet
What You'll Add to DigitalOcean:
  • 5+ years of experience in capacity planning, infrastructure operations, or a related technical/analytical role
  • Strong understanding of the current GPU hardware market - models, vendors, availability, and performance characteristics
  • Familiarity with serverless inference workloads and spot capacity dynamics
  • Experience analyzing usage and demand data to drive resource allocation or optimization decisions
  • Strong foundation with SQL and data visualization tools (e.g. Looker, Grafana) to build reporting and models
  • Experience with, and strong interest in building, automation/tooling/AI agents to reduce manual analysis
  • Working knowledge of data center rack and power capacity planning concepts
  • Strong cross-functional communication skills, with experience partnering across DCOPS, Network Engineering, Product, and Delivery
  • Bonus: experience with data center inventory tools such as dcTrack or Netbox
Compensation Range:
  • $106,000 - $132,000

*This is a hybrid role



#LI-Hybrid

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