Global Supply Manager
NVIDIA
Global Supply Manager
NVIDIA
Designs the chips and software that power AI
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people on the planet working for us. If you're creative and autonomous, we want to hear from you!
We are now seeking a senior level supply chain management professional – Global Supply Manager (GSM) to lead materials readiness, supply visibility, and Clear-to-Build (CTB) execution for complex networking product. This role is responsible for ensuring turnkey materials do not become a constraint to critical AI infrastructure high volume products, while driving stronger planning discipline, faster shortage resolution, and better decision-making through data, automation, and AI-enabled workflows. The successful candidate will work closely with Global commodity team, Engineering, Contract Manufacturers (CMs), and component Suppliers to improve material availability, strengthen operational processes, and build scalable reporting and analytics. This is a highly cross-functional role that requires strong supply chain judgment, structured problem-solving, and the ability to turn data into action.
What you’ll be doing:
Own the Clear-to-Build (CTB) process, providing clear visibility to material readiness, projected coverage, and key constraints that may impact build plans and customer commitments.
Partner with CMs, suppliers, distributors, Global Commodity team (GCM) and Engineering to manage material risk, resolve shortages, and prevent turnkey materials from landing on the critical path.
Serve as a senior escalation point for material issues from the CMs, driving timely actions on expedites, recovery plans, and alternate supply or engineering solutions through closure.
Review and strengthen CM materials management processes, including controls for supply-demand alignment, site balance, safety stock, and excess and obsolete (E&O) mitigation.
Drive accountability for accurate and timely supply-demand reporting from CMs, with clear follow-up on critical shortages, gaps, and recovery actions.
Lead continuous improvement initiatives that reduce lead times, improve material availability, and increase overall supply chain efficiency and execution quality.
Build and enhance data intelligence capabilities using tools such as Power BI and modern AI / low-code platforms to improve visibility, analysis, reporting, and collaboration across internal teams and external partners.
Prepare executive-ready updates on material availability, supply risk, and key performance indicators for cross-functional and leadership reviews.
What we need to see:
Bachelor’s degree or equivalent experience in supply chain, operations, industrial engineering, business, or a related field.
10+ years of recent experience in materials planning, materials management, or supply chain operations, particularly on PCBA board/ system products or Optics module/ systems, with in-depth understanding on EE, Mechanical, interconnector supply base.
Strong experience with EMS industry supply chain processes and Contract Manufacturer management.
Proven ability to solve complex operational problems and influence stakeholders through data, structured analysis, and clear communication.
Strong analytical and quantitative skills, including advanced Excel, data modeling, forecasting, scenario analysis, predictive or statistical analysis, and clear communication of supply chain metrics.
Hands-on experience with BI, automation, or AI-enabled tools; experience with low-code or no-code platforms and modern productivity AI tools is a strong plus.
Strong written and verbal communication skills in English, with the ability to present effectively to executive management.
NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.
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