NVIDIA Corporation

Principal Performance and Manufacturing Architect

NVIDIA Corporation • $232K — $368K *
US-Anywhere
+ 6 other locationsRemote
Manufacturing & Automotive
11 - 15 years of experience
Reposted 1 week ago
Job Overview by Ladders

Qualifications

  • BSEE / MSEE / PhD or equivalent experience with 15+ years in the field.
  • Hands-on understanding of transient voltage fluctuation behavior and how it affects stress conditions.
  • Experience building first-principles models connecting physical parameters to manufacturing outcomes.
  • Track record of defining manufacturing test specifications on a shipped product with accountability for margin terms.
  • Experience running silicon validation experiments that demonstrate the robustness of models from development through production.

Responsibilities

  • Own the understanding of physics linking mechanisms to yield and defect margins.
  • Define and specify testing parameters to capture worst-case conditions through assembly.
  • Create and maintain the authoritative documentation for methodologies across engineering teams.
  • Develop and oversee validation plans that include experimental designs and monitoring criteria.

Benefits

  • Eligibility for equity participation.
  • Comprehensive benefits package including health and wellness programs.
  • Access to company resources aimed at employee development.
  • Flexible work arrangements to support work-life balance.
Full Job Description
We are looking for a Principal Performance and Manufacturing Architect who has built the models, defined the specs, and seen them validated through silicon. You have owned the connection between design intent and manufacturing reality, not as a reviewer or a contributor, but as the person who set the methodology and proved it worked. You turn ambiguous physical phenomena into quantified, defensible margin terms. You do not wait for data to confirm your hypothesis; you design the experiment that gets it. You improve how the organization ships products after every program.

The exceptional hire also uses AI deliberately - with proven workflow impact and the judgment to know where it compresses real work and where it introduces risk.

What you'll be doing:

  • Own the physics, from mechanism to margin. Build first-principles models connecting AVF, defect mechanisms, and DVFS transients to field FIT, system-level yield, and DPPM vs. coverage - calibrated per node and population shift - so every margin term in the V/F curve and P-state table is named, sourced, and defensible.
  • Set the screen that resolves escapes. Specify ATE and SLT voltage, frequency, and timing conditions that capture worst-case transient VF windows - making it unambiguous whether a marginal defect or timing violation is detected or escapes at every manufacturing stage.
  • Make the POR the authoritative source. Author the methodology document for each program and drive alignment across build, product definition, reliability, and test engineering - so every team is making decisions from the same model.
  • Prove the model before production. Own the per-release validation plan - split-screen experiments, sample sizes, statistical acceptance criteria, and production monitoring - through QS sign-off.


What we need to see:

  • BSEE / MSEE / PhD or equivalent experience, with 15+ years in the field.
  • Deep, hands-on understanding of how transient VF behavior develops worst-case stress conditions for marginal defects and timing violations - you know the mechanisms, not just the models.
  • Demonstrated experience building first-principles models connecting physical parameters to manufacturing outcomes, calibrated through real silicon.
  • A clear track record defining manufacturing test specifications on a shipped product, with each margin term explicitly sourced and owned.
  • Built and ran silicon validation experiments that proved models from NPI through production, not as a supporting contributor, but as the person who developed and was responsible for the experiments.


Ways to stand out from the crowd:

  • You have applied AI to production engineering workflows - model fitting, anomaly detection, and specification generation - and can describe the outcomes and the guardrails you put in place.
  • Worked across the VF specification and manufacturing boundary on multiple nodes and can articulate how your approach evolved as defect populations shifted.
  • Led multi-functional alignment on a methodology disagreement and brought the organization to a defensible, shared decision.
  • Delivered innovative solutions on programs where the schedule did not allow a second experiment.


Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 232,000 USD - 368,000 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 29, 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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