NVIDIA is seeking an elite, hands-on Principal Engineer who specializes in supply network simulation. This person will serve as the core technical architect and strategic partner to our Vice President. In this critical individual contributor role, you will not manage a team. You will personally own and compose highly complex mathematical models that dictate our global hardware procurement strategy.
Your models will directly simulate and forecast our demand for fundamental technology elements, including semiconductor wafers, memory devices, substrates, and key sub-assemblies that require lengthy procurement periods. You must be an absolute modeling purist who thrives on extreme detail and possesses deep technical coding skills. Your role includes future-proofing our infrastructure by improving deterministic systems with modern AI capabilities. Does this sound like your dream job? If passionate about supply chain and working at the forefront of the AI revolution, come show us what you got!
What you’ll be doing:
End-to-End Code Execution: Personally write, debug, and scale advanced simulation models in Python, MATLAB, and Excel from scratch.
AI Augmentation: Upgrade traditional simulations by building and deploying Machine Learning (ML) and AI models to predict supply anomalies, market disruptions, and non-linear demand shifts.
Material Forecasting: Build deterministic and stochastic models to simulate multi-variable demand scenarios for silicon wafers, memory, substrates, and critical long-lead-time sub-assemblies.
Executive Partnership: Translate complex algorithmic and AI-driven outputs into clear, actionable financial and operational recommendations directly for the VP.
Data Integrity & Architecture: Audit massive datasets to ensure extreme precision, as your model outputs will directly commit millions of dollars in spend.
Continuous Optimization: Constantly stress-test, refine, and modernize legacy planning sheets into automated, high-performance computing scripts.
Partnership: Partner closely with supply chain, procurement, finance, and engineering teams to evaluate scenario-based planning and long-range sourcing strategies.
What we need to see:
Bachelor’s degree within Operations Research, Industrial Engineering, Computer Science, Data Science, Mathematics, Statistics, Physics, or an equivalent quantitative engineering discipline (or equivalent experience).
Expert Modeling & Coding: Proficiency in Python (specifically libraries like Pandas, NumPy, SciPy) and MATLAB is non-negotiable.
15+ Years of Quantitative Experience: with Proven track record of personally building, running, and deploying complex mathematical, simulation, or financial models.
Hands-on AI/ML Experience: 2+ years of practical, hands-on experience designing, training, and deploying AI or algorithms based on learning from data (not just theoretical knowledge).
Ability to build complex, formula-dense spreadsheets, macro automation, and data models where rapid prototyping is required.
Extreme Detail Orientation: Demonstrated success in identifying edge-case anomalies in massive datasets that others miss.
Demonstrated experience presenting raw data and model architectures directly to VP-level leadership.
Ways to stand out from the crowd:
Advanced degree (Master’s or PhD) with a focus on optimization, simulation, or machine learning, or equivalent experience.
Prior background in the technology hardware, semiconductor, or electronics supply chain sectors.
Familiarity with capacity planning, inventory theory, or procurement logistics.
Experience deploying AI models into live cloud environments (e.g., AWS, Azure, GCP).
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- Bachelor's degree in Operations Research, Industrial Engineering, Computer Science, Data Science, Mathematics, Statistics, Physics, or equivalent experience
- Expert proficiency in Python (including Pandas, NumPy, SciPy)
- Proficiency in MATLAB
- Advanced Excel skills including formula-dense spreadsheets and macro automation
- 15+ years of quantitative experience building, running, and deploying complex mathematical, simulation, or financial models
- 2+ years hands-on experience designing, training, and deploying AI/ML models from data
- Demonstrated extreme attention to detail and ability to identify edge-case anomalies in massive datasets
- Experience presenting raw data and model architectures directly to VP-level leadership
- Advanced degree (Master's or PhD) in optimization, simulation, or machine learning
- Prior experience in technology hardware, semiconductor, or electronics supply chain
- Familiarity with capacity planning, inventory theory, or procurement logistics
- Experience deploying AI models into live cloud environments (AWS, Azure, GCP)
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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