Principal Performance and Manufacturing Architect
Brief Overview
NVIDIA is seeking a Principal Performance and Manufacturing Architect to join their Silicon Co-Design Group. This role requires deep expertise in building models, defining specs, and validating them through silicon. The ideal candidate will own the connection between design intent and manufacturing reality, setting methodologies and proving them through silicon.
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.
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.
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.
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—knowing the mechanisms, not just the models.
Demonstrated experience building first-principles models connecting physical parameters to manufacturing outcomes, calibrated through real silicon.
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
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.
Company Information
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, NVIDIA is committed to fostering an inclusive work environment and is proud to be an equal opportunity employer. NVIDIA uses AI tools in its recruiting processes. The company is dedicated to fostering an inclusive work environment and is committed to equal employment opportunities regardless 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. Applications for this job will be accepted at least until June 29, 2026. This posting is for an existing vacancy.