TPM

What you'll own

• Capacity planning and forecasting: Build and maintain the 6/12/26-week rolling capacity model across every cluster. Translate customer contracts and sales pipeline into capacity requirements. Forecast model replicas, system-hours, and spares. Reconcile against actuals weekly and maintain the source-of-truth document.
• New Datacenter Capacity bring-up: Collaborate with datacenter infrastructure and operations teams to support new datacenter bring-up, ensure production readiness, drive engineering efforts and automation for on-time delivery.
• Allocation and cluster placement: Partner with SRE and product teams to run weekly capacity reviews. Decide model placement, re-balancing, customer tenant assignments, cluster absorption of new launches, and freezes. Run weekly capacity and utilization reports. Drive downstream model deployment tasks with SRE.
• Drive capacity planning tool adoption: Partner with console engineering to drive stakeholder adoption of the in-house capacity planning and allocation tool (user acceptance testing, issue resolution, tracking changes, pilot testing, deployment). Contribute to continuous process improvement and development of internal capacity management tools.
• Incident tracking and postmortems: Proactively identify and mitigate capacity bottlenecks, risks, and dependencies. Drive resolution and postmortems for SLA drops due to capacity misallocations.

Key Responsibilities

• Run weekly capacity planning and daily capacity and deployment tracking with Engineering, Product, and Operations teams.
• Own fleet utilization reporting and forecasting.
• Drive capacity planning for new customer deployments and major model launches.
• Drive continuous improvement and stakeholder adoption of new capacity management platform.
• Drive org-level strategic initiatives related to capacity expansion, improving fleet efficiency, and maximizing utilization of available systems.
• Lead planning around major infrastructure events (new customer commits, new model releases, changes to DC/cluster architecture) that impact capacity and fleet utilization; update plans and forecasts accordingly.
• Maintain Jira EPICs and Confluence pages related to capacity planning, reporting, and change management for execution transparency.

Qualifications

• 5+ years of TPM, technical program management, or product operations experience in cloud infrastructure, large-scale ML serving, or hyperscaler capacity planning.
• Experience leading large cross-functional programs involving Engineering, Product, and Operations.
• Comfort with the inference serving stack: model replicas, batching, prefill/decode, KV cache, accelerator scheduling.
• Strong data fluency: SQL, Grafana, basic Python or Flux to pull your own numbers.
• Track record of running a recurring cross-functional ritual involving senior engineers and leadership.
• Direct experience with AI accelerator fleet operations such as Habana, TPU pods, Inferentia, Trainium.