Nvidia Senior Manager Materials Planning Management 

United States, California 

638815555

What you will be doing:

• Lead, mentor, and develop an impactful team of Materials Planners by defining objectives, priorities, and performance metrics aligned with organizational objectives, with a focus on strategic engagement and data-driven decision-making

• Lead BOM risk review meetings with cross-functional teams to identify single/sole-source, EOL, and long-lead components; track and mitigate risks throughout the program.

• Drive multi-source qualification for critical components and track to closure before production release.

• Define and implement materials mitigation strategies including safety stock, buffers, and vendor-managed inventory (VMI) hubs across regions

• Collaborate with Engineering to assess and implement early procurement for long-lead and high-risk components (“risk buys”)

• Lead materials readiness reviews with CMs to ensure clear-to-build status aligned with build plans and production schedules.

• Employ digital tools to improve supplier collaboration and streamline procurement processes across all global regions.

• Establish and monitor critical metrics, using digital dashboards for real-time tracking of materials readiness and supply versus demand performance, and lead the change management process to evolve planner roles into AI-augmented decision-makers.

What we need to see:

• Bachelor’s degree or higher in Supply Chain, Data Analytics, Operations, Engineering, or a related field with equivalent experience.

• Minimum of 12 overall years of experience (with 6+ years managing a team) in materials management, procurement, or supply chain management within a semiconductor OEM environment.

• Deep understanding of supply chain processes, BOM structures, NPI lifecycle, CM management, and electronic component supply chains, is required.

• Proficiency with ERP/MRP systems (e.g., SAP, Oracle), PLM systems (e.g., Windchill PDP, Agile), and supply chain analytics tools.

• Strong technical knowledge of semiconductors, turnkey materials, and contract manufacturing processes.

• Excellent communication, collaboration, and cross-functional leadership skills.

• Familiarity with Agentic AI concepts (e.g., autonomous agents for decision support, event-driven workflows, exception management).

• Experience using or implementing AI planning tools (e.g., Kinaxis, o9, Blue Yonder) or LLM-based copilots for BOM or CTB planning.

• Ability to collaborate with Data Science teams to define use cases, train models, and refine AI agent behavior.

• Comfortable interpreting AI-generated insights and integrating them into business processes and communication.