NVIDIA

1 month ago

Principal Performance and Manufacturing Architect

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 40 minutes agoStatus: Live

Job Summary

Lead the development of first-principles models connecting hardware physics to manufacturing outcomes, defining methodology across design, reliability, and test engineering, and validating models through silicon production. Use AI to improve production workflows, design experiments to bound margins, and align multi-functional teams to ensure margin integrity from NPI to production.

Location: Santa Clara

Workplace: Onsite

Employment Type: Full time

Job Function: Manufacturing & Production Operations

Key Responsibilities

•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.
•Deliver the payoff that every NVIDIA product ships through the systems you’ll help build by validating models from NPI through production and leading experiments that ensure margins hold through production.

Pay and Benefits

Salary: USD 232,000 - 368,000 annually

Perks:EquityBenefits

Key Requirements

•BSEE / MSEE / PhD or equivalent experience, with 15+ years in the field.

Experience:15+ yearsSemiconductorsManufacturingAI in manufacturing

Education:PhD / Doctorate

Skills:ModelingExperimental designSilicon validationStatistical analysis

Tech Stack:AIMachine learningFirst-principles modelingDVFSVF

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

1 month ago

Principal Performance and Manufacturing Architect

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 40 minutes agoStatus: Live

Job Summary

Location: Santa Clara

Workplace: Onsite

Employment Type: Full time

Job Function: Manufacturing & Production Operations

Key Responsibilities

•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.
•Deliver the payoff that every NVIDIA product ships through the systems you’ll help build by validating models from NPI through production and leading experiments that ensure margins hold through production.

Pay and Benefits

Salary: USD 232,000 - 368,000 annually

Perks:EquityBenefits

Key Requirements

•BSEE / MSEE / PhD or equivalent experience, with 15+ years in the field.

Experience:15+ yearsSemiconductorsManufacturingAI in manufacturing

Education:PhD / Doctorate

Skills:ModelingExperimental designSilicon validationStatistical analysis

Tech Stack:AIMachine learningFirst-principles modelingDVFSVF

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor