Technical Program Manager, NPI Capacity and Constraints Management
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- Dublin
- Permanent
- Full-time
- Bachelor's degree in a technical field, or equivalent practical experience.
- 2 years of experience in program management.
- Experience with data center infrastructure like power, networking, and cooling.
- Experience with AutoCAD or Revit.
- Bachelor's, Master's or PhD degree in Electrical, Civil, Architectural, or Mechanical Engineering.
- Experience managing data center constraints and knowledge of colocation data center physical layouts, infrastructure, and standards (power, space, cooling, operations and network).
- Experience with data center, networking and machine deployments, including understanding of deployment process and the ability to drive tools and automation for continuous process improvement.
- Experience with colocation capacity planning, including the use and automation of planning and optimization tools.
- Familiarity with new product introduction (NPI) process and Product Life Cycle (PLC), particularly as related to hardware products for machine learning and high-performance computing.
- Support the delivery of large, complex projects, managing data center constraints (power, space, cooling, operations and network) in colocation data center deployments. This role in particular will have a focus on colocation NPI deployments, particularly for high-performance computing initiatives.
- Create and manage physical layouts and standards, including the deployment impact and feasibility of NPIs. Define and manage tooling requirements for planning and delivery.
- Own and nurture relationships between cross-functional teams. Track deployment workflows with partner teams and raise issues proactively to ensure on-time follow-through.
- Influence the development of NPI and colocation server floor design decisions, focused on upcoming fleetwide transitions in the ML and accelerator space. Build plans to help transition between successive product generations.
- Define standards and policies to simplify deployability of new ML and accelerator products, spanning TPU, GPU, and other product families.