NVIDIA

NVIDIA

Posted via Workday

Principal Performance and Manufacturing Architect

Posted Aug 5, 2026

Role at a glance

Job function
Engineering & R&D Semiconductor & Display Engineering
Salary
Not Disclosed
Location
6 Locations, California, United States
Work arrangement
Hybrid
Employment
Full-time
Experience
15+ years in the field.
Education
BSEE / MSEE / PhD or equivalent experience

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Qualifications

BSEE, MSEE, PhD, or equivalent experience; 15+ years in the field; hands-on understanding of transient VF behavior and its effects on marginal defects and timing violations; experience building first-principles models calibrated through real silicon; a track record defining manufacturing test specifications for shipped products; and ownership of silicon validation experiments from NPI through production.

Required

  • BSEE / MSEE / PhD or equivalent experience
  • 15+ years in the field
  • Deep, hands-on understanding of transient VF behavior and how it develops worst-case stress conditions for marginal defects and timing...
  • Experience building first-principles models connecting physical parameters to manufacturing outcomes, calibrated through real silicon
  • Track record defining manufacturing test specifications on a shipped product, with each margin term explicitly sourced and owned
  • Built and ran silicon validation experiments proving models from NPI through production, as the person who developed and was responsible...

Preferred

  • Applied AI to production engineering workflows such as model fitting, anomaly detection, and specification generation, with demonstrable...
  • Worked across the VF specification and manufacturing boundary on multiple nodes and can explain how the approach evolved as defect...
  • Led cross-functional alignment on a methodology disagreement and reached a defensible shared decision
  • Delivered innovative solutions on programs where the schedule did not allow a second experiment

About the role

Original posting provided by NVIDIA

View original

NVIDIA’s Silicon Co-Design Group sits at the crossroads of architecture, silicon, systems, and manufacturing, where first-principles thinking and engineering judgment at the highest level translate directly into product outcomes at scale.

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.

The payoff is that every product NVIDIA ships goes through the systems you'll help build. If that's the kind of problem you want to work on, we'd like to talk! NVIDIA is widely considered one of the technology world’s most desirable employers — home to some of the most forward-thinking engineers in the industry. If you build models others depend on, set specifications that hold up through production, and make the next program better because of what you learned, we want to hear from you.

 

#LI-Hybrid

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 September 27, 2026.

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.

NVIDIA

About the company

NVIDIA

Large Enterprise

NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.