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Modeling Engineer, Supply Chain Optimization

NVIDIA· Data Scientist
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Santa Clara, CA$168k - $264.5kFull-timePosted 1mo ago

About the role

Quantitative optimization modeler responsible for owning and extending a proprietary linear programming based production model to optimize NVIDIA's supply chain, with potential augmentation by AI and GPU-accelerated 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.

Qualifications

  • Master’s degree or PhD in Operations Research, Industrial Engineering, Applied Mathematics, Management Science, or closely related quantitative field (or equivalent experience).
  • Minimum of 8 years of experience in a higher education, modeling, engineering, or data science position.
  • Strong hands-on experience formulating and solving linear programming or mixed-integer programming problems, including developing objective functions and constraints and extracting and interpreting dual variables.
  • Deep understanding of constrained optimization and LP/MIP fundamentals (duality, shadow prices, sensitivity analysis, degeneracy, numerical conditioning, solver behavior).
  • Proficiency in mathematical optimization techniques and scientific computing with production or research optimization models in MATLAB, Julia, R, Python, or comparable environments.
  • Understanding of supply chain concepts (bills of materials, capacity constraints, lead times, yields, allocation decisions, multi-period planning).
  • Ability to translate complex systems into rigorous mathematical formulations and communicate results to analytical and operational partners.
  • Demonstrated hands-on, end-to-end ownership of complex quantitative work while collaborating with senior colleagues.

Skills

Required:Linear programming (LP) / Mixed-integer programming (MIP)Mathematical optimization techniquesScientific computingSupply chain conceptsCommunication with cross-functional teams

Benefits

  • Equity
  • Benefits (see company benefits link)
Last updated Sep 18, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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