Senior Director, Hardware Reliability & AI-Driven Strategy

NVIDIA Corporation; Santa Clara (CA); On-site; USD 332,000 - 500,000; Full time

Job summary

NVIDIA Corporation seeks a Sr. Director of Board and System Level Reliability to set engineering standards for reliability across boards and systems.

You will lead global teams, influence design and supply chain decisions, and advance AI-driven reliability frameworks. This senior role requires deep expertise in physics of failure, reliability testing, and statistical modeling, with emphasis on scalability across data centers and automotive platforms.

Qualifications

• Bachelor's degree in Engineering, Physics, Materials Science, or related field; Graduate degree preferred.
• 18+ years in board and system-level reliability testing and activities.
• 5+ years in Data Center equipment reliability and 10+ years leading reliability management.
• Deep understanding of reliability concepts, physics of failure, testing methodologies, and industry standards.

Responsibilities

• Own board and system level hardware reliability across product lines (Data Center, Server, Graphics, Automotive, Embedded).
• Lead reliability labs and multiple multidisciplinary teams across sites.
• Develop and implement company-wide HW reliability strategies.
• Drive DfR, DfX, reliability modeling, and risk assessments.

Skills

Board reliability

System-level testing

DfR (Design for Reliability)

FMEA

Reliability modeling

Statistics

Data-driven decision making

Education

Bachelor's degree in Engineering or related field

Graduate degree preferred

Tools

Finite element analysis

Semiconductor/device testing

Job description

NVIDIA Corporation seeks a Sr. Director of Board and System Level Reliability to set engineering standards for reliability across boards and systems.

You will lead global teams, influence design and supply chain decisions, and advance AI-driven reliability frameworks. This senior role requires deep expertise in physics of failure, reliability testing, and statistical modeling, with emphasis on scalability across data centers and automotive platforms.