Modeling Engineer, Supply Chain Optimization

Responsibilities

• Own and extend a production linear programming optimization model.
• Develop constraint matrices, objective functions, dual-variable extraction logic, and diagnostics.
• Maintain a rigorous grasp of the system's mathematical behavior.
• Translate evolving physical supply chain realities — including new wafer nodes, packaging architectures, component categories, capacity limits, yields, and lead times — into mathematical formulations the optimization engine can solve.
• Analyze shadow prices, sensitivities, and other LP diagnostics to identify the economic impact of supply constraints and turn model results into actionable insights for executive planning, procurement, and supplier discussions.
• Maintain the integrity of model inputs and assumptions, understanding data lineage, schemas, dependencies, and the downstream implications of changes or inaccuracies.
• Partner directly with supply chain, procurement, operations, and engineering teams to identify high-value planning decisions, quantify constraints, stress-test assumptions, and develop scenarios that improve supply and resource management.
• Serve as a quantitative thought partner to senior supply chain leadership, challenging assumptions, evaluating boundary conditions, and evolving the model architecture as NVIDIA’s products and supply network become increasingly complex.
• Explore opportunities to augment the deterministic optimization foundation with AI, machine learning, GPU-accelerated optimization, and NVIDIA technologies such as cuOpt.
• What we need to see

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