T

TensorWave

Scalable AI cloud computing for PyTorch

Head of GPU Capacity Planning

Supply Chain ManagementConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 5 years of experience in capacity planning, supply and demand planning, sales and operations planning, technical program management, or infrastructure operations; experience in cloud, data center, or hardware-intensive environments is ideal.
  • Working knowledge of data center and compute infrastructure fundamentals, including racks, power and cooling constraints, servers and GPUs, and networking, with the ability to reason about physical and logical capacity.
  • Advanced modeling skills and the ability to build forecasting and allocation models; data fluency is required, with SQL and business intelligence tools noted as a plus.
  • A track record of working across Sales, Finance, and Operations and translating technical constraints into actionable commercial guidance.
  • Written communication skills and the discipline to run a recurring operating cadence and produce clear, trusted reporting.

Responsibilities

  • Maintain a single source of truth for total, committed, reserved, and available-to-sell capacity across every site and GPU generation, reconciling physical fleet inventory—including installed, in-burn-in, spare, and return merchandise authorization units—against logical and contracted allocations.
  • Standardize how capacity is defined, measured, and reported so definitions are consistent and stakeholders use the same figures.
  • Own the demand pipeline and track contracted ramp curves, steady-state consumption, expiries, renewal probability, and take-or-pay floors, while maintaining weighted pipeline separately from committed capacity.
  • Define and publish sellable capacity by site, GPU type, and timeframe, and provide Sales with a current view of what can be committed and when.
  • Partner with Sales and Deal Desk across active deals to validate feasibility before commitments, flagging oversubscription risk and allocation conflicts early.
  • Own the multi-year capacity strategy and coordinate Infrastructure Operations, Sales, Finance, and leadership to ensure the long-range plan reflects actual fleet capability.
  • Anticipate capacity constraints quarters ahead and drive cross-functional decisions on deployments, reservations, and site expansion to meet demand.
  • Own the buffer and oversubscription policy with Operations and Finance, and keep the rules visible and enforced.
  • Translate sales pipeline and contracted growth into a rolling capacity forecast, identifying shortfalls and the lead time needed to address them.
  • Coordinate with Infrastructure Operations, Global Operations, and supply chain on incoming racks, nodes, power, cooling, and network capacity so delivery timelines align with committed and forecast demand.
  • Connect Operations, Sales, Finance, the Project Management Office, and data center teams around a unified capacity plan.
  • Run the weekly capacity review and produce the weekly capacity report and dashboard for leadership, Sales, and Finance.
  • Track committed versus available capacity weekly, maintaining an auditable record of allocations, changes, and the decisions behind them.
  • Assess and improve capacity planning processes, document standards and workflows, and increase planning maturity.
  • Define and prioritize tooling requirements for capacity, inventory, and allocation systems, including data center infrastructure management systems, dashboards, and tracking tools, and partner with IT, Engineering, and vendors on build-versus-buy decisions.

Desired Qualifications

  • Experience in GPU cloud, high-performance computing, hyperscale, colocation, or semiconductor capacity environments.
  • Familiarity with Slurm and Kubernetes cluster capacity, GPU fleet management, and utilization metrics.
  • Experience writing requirements for and standing up data center infrastructure management, capacity, or inventory tooling.
  • Program management certification, such as Project Management Professional or equivalent.

About the Company

TensorWave

Scalable AI cloud computing for PyTorch

TensorWave provides cloud-based compute power for large-scale AI workloads, with a focus on PyTorch. It runs on AMD MI300X hardware with a scalable fabric that can pool vast amounts of VRAM, and customers access this power through a subscription or pay-as-you-go model. The service allocates the requested compute and storage behind a managed fabric, charging based on usage to offer flexibility and cost-efficiency. TensorWave aims to be a leading AI cloud provider by offering large VRAM pools and strong price‑to‑performance, helping enterprises and research institutions train, fine-tune, and deploy large models without owning hardware.

Company size
51-200
Company stage
Series B
Total funding
$493M
Headquarters
Las Vegas, NV
Founded
2023

Recently Posted Jobs

Explore more opportunities at TensorWave

See more jobs