NVIDIA Corporation

Modeling Engineer, Supply Chain Optimization

NVIDIA Corporation • $168K — $322K *
Santa Clara, CA 95051In-Person
Business Services
8 - 10 years of experience
Today
Be an Early Applicant
Job Overview by Ladders

Qualifications

  • Master's degree or PhD in Operations Research, Industrial Engineering, Applied Mathematics, Management Science, or a related field, or equivalent experience.
  • Minimum of 8 years in modeling, engineering, or data science roles.
  • Experience in formulating and solving linear or mixed-integer programming problems.
  • Deep understanding of constrained optimization principles and mathematical foundations of LP/MIP.
  • Proficiency in scientific computing and optimization techniques; experience with MATLAB, Julia, R, Python, or similar environments.
  • Knowledge of supply chain modeling concepts, such as bills of materials and capacity constraints.
  • Ability to articulate complex mathematical concepts to diverse teams.

Responsibilities

  • Own and extend a production linear programming optimization model, developing key components like constraint matrices and objective functions.
  • Translate physical supply chain changes into mathematical formulations for optimization.
  • Analyze LP diagnostics to derive actionable insights for planning and procurement.
  • Maintain model integrity by understanding data lineage and the implications of changes.
  • Collaborate with cross-functional teams to identify key planning decisions and quantify constraints.
  • Serve as a quantitative thought partner to supply chain leadership, evolving model architecture with complexity.
  • Explore integration of AI and machine learning into existing optimization models.

Benefits

  • Eligibility for equity participation.
  • Comprehensive benefits package including health insurance options.
  • Professional development opportunities in a cutting-edge technological environment.
  • Supportive team culture that prioritizes collaboration and innovation.
Full Job Description
We are looking for a deeply quantitative optimization modeler who can take ownership of this production model, extend its mathematical capabilities, and ultimately become the technical authority for its optimization architecture. This is an opportunity for someone who sees supply chain planning fundamentally as a mathematical modeling problem and wants their work to directly influence consequential decisions at the frontier of AI infrastructure. Does this sound like a great new adventure? Then come show us what you've got!

What you'll be doing:
  • 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:
  • Master's degree or PhD in the field of Operations Research, Industrial Engineering, Applied Mathematics, Management Science, or a closely related quantitative subject area, or equivalent experience.
  • A 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 direct experience developing objective functions and constraints and extracting and interpreting dual variables.
  • Deep understanding of constrained optimization and the mathematical foundations underlying LP/MIP, including duality, shadow prices, sensitivity analysis, degeneracy, numerical conditioning, and solver behavior.
  • Strong scientific computing skills combined with proficiency in mathematical optimization techniques, with experience implementing production or research optimization models in MATLAB, Julia, R, Python, or comparable quantitative computing environments.
  • Understanding of supply chain modeling concepts such as bills of materials, capacity constraints, lead times, yields, allocation decisions, and multi-period planning.
  • Ability to translate complex physical or organizational systems into rigorous mathematical formulations and explain model assumptions, behavior, tradeoffs, and results to both analytical and operational collaborators.
  • Demonstrated ability to operate as a highly hands-on individual contributor, taking end-to-end ownership of complex quantitative work while collaborating effectively with senior engineering and commercial partners.


Ways to stand out from the crowd:
  • Advanced research or publications in operations research, mathematical optimization, supply chain optimization, prioritization, or related fields, including work presented through INFORMS, IISE, or peer-reviewed journals.
  • Deep experience with LP/MIP solvers and mathematical programming environments such as MATLAB Optimization Toolbox, Gurobi, CPLEX, or similar technologies, including interpretation of dual variables and solver diagnostics beyond basic model execution.
  • Experience developing optimization models using real-world manufacturing or supply chain data, particularly models involving semiconductor capacity, wafer starts, yields, advanced packaging, substrates, PCBs, or other hardware constraints.
  • Experience with semiconductor, electronics, or AI infrastructure supply chains and an understanding of the relationships among manufacturing capacity, component availability, product demand, and revenue opportunity.
  • Familiarity with NVIDIA cuOpt, GPU-accelerated optimization, or techniques that combine deterministic optimization with AI or machine learning.


Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 200,000 USD - 322,000 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 19, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

About NVIDIA Corporation

Nvidia, a global leader in graphics, gaming, and AI technology, offers Nvidia careers and internship opportunities for those passionate about driving innovation in the tech industry. you'll find a company committed to growth, teamwork, and leadership in computer science and machine learning domains.

About Nvidia

A Pioneer in Technology and Innovation

Nvidia has cemented its reputation as a powerhouse in developing advanced graphics processing units (GPUs) and has significantly contributed to the gaming industry's evolution. Moreover, its foray into AI and machine learning has opened new frontiers in technology, making Nvidia a beacon of innovation and a desirable workplace for ambitious tech professionals.

Job Opportunities

Diverse Positions in a Dynamic Field

Nvidia is continuously on the lookout for talented individuals across various domains, including hardware and software engineering, product design, marketing, and sales. Employment opportunities at Nvidia are vast, catering to a wide range of expertise and career aspirations.

Employment in Hardware and Graphics

For those fascinated by the intricacies of hardware and graphics technology, Nvidia offers positions that sit at the forefront of gaming and computing advancements.

Growth in Machine Learning and AI

Nvidia's leadership in AI and machine learning has created numerous vacancies for specialists eager to contribute to groundbreaking projects.

Recruitment in Computer Science

With the constant demand for innovation, Nvidia's recruitment efforts focus on computer science experts capable of pushing the boundaries of what's possible.

Internship Program

Opening Doors to Future Innovators

Nvidia's internship program is designed to nurture the next generation of technology leaders, offering hands-on experience in a culture that celebrates creativity and teamwork.

Benefits and Culture

Interns at Nvidia enjoy a plethora of benefits, from competitive stipends to mentorship opportunities, all within an environment that values growth and learning.

Opportunities for Students

Whether you're an undergraduate, a master's student, or a Ph.D. candidate, Nvidia's internships provide a real-world glimpse into the tech industry, offering valuable experience in various technology fields.

Pathways to Full-Time Employment

Many interns have transitioned into full-time positions, marking the start of successful careers at Nvidia. The internship program is more than a stepping stone into the company; it’s an investment in the professional development of interns. The goal is to ensure that interns are well-equipped for future challenges.

Nvidia Careers: More Than Just a Job

Nvidia offers more than just a job to its employees; it provides a front-row seat on the journey into the future of technology. Nvidia stands as a pillar of innovation with its vast opportunities in hardware, graphics, gaming, machine learning, and computer science. Nvidia careers serve as a launching pad for talented workers who aim to redefine the technological landscape. Whether through full-time positions or internships, joining Nvidia means contributing to a legacy of breakthroughs and becoming part of a global community dedicated to pushing the boundaries of what's possible.
Learn more about NVIDIA Corporation
Size
22,473 employees
Market Cap
$350.4 billion
Industry
Manufacturing & Automotive
Net Income
$4.3 billion
Founded
1993
5 Year Trend
+31.3%
Revenue
$16.6 billion
NASDAQ
NVDA
* Ladders Estimates

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