We are looking for a system engineer to join our Failure Analysis engineering team under the System Product Engineering group in the NVIDIA. As a System Failure Analysis (FA) Engineer, you are responsible for the end-to-end investigation of product failures. You act as the Failure analysis product owner diagnosing complex issues that span Hardware, Software, Firmware, and Mechanical boundaries of the investigation, synthesizing data from all engineering disciplines to reach a definitive root cause. While you provide the architectural oversight for the team, you remain deeply technical and active in the laboratory environment.
What You’ll Be Doing:
Hands-on Lab Investigation: You are active in the lab environment. You perform advanced debugging, characterize system behavior, run reproductions of failures in the lab, and utilize sophisticated lab equipment to validate hypotheses, bridging the gap between high-level data and physical hardware reality.
Multidisciplinary Failure Analysis: Lead deep-dive investigations into system-level failures, understand and analyse customer usage for the product, diagnose how software execution, firmware logic, and hardware components interact to cause specific failure modes.
Root Cause Ownership: Drive the investigation lifecycle from initial symptom to final physics-of-failure or logic-error identification.
Task Force Leadership: Orchestrate and lead cross-organizational technical task forces at the company level. You align experts from HW, SW, Mechanical, and NPI teams to solve high-priority technical problems.
Advanced Data & AI Integration: Define and utilize sophisticated data analysis tools and AI-driven methodologies. You correlate customer failure patterns with production telemetry and RMA history to identify hidden trends and systemic risks.
Customer Quality Support: Take part in the customer interface by interacting with NVIDIA’s Customer Quality Engineers. You provide the deep technical evidence and root-cause clarity needed for quality reports and high-level technical presentations.
Strategic Lab Direction: Define the high-level debug strategy and complex test plans for the lab. You guide hardware practical engineers on characterization requirements and system-level stress testing.
What We Need to See:
Lab Proficiency: Expert-level experience with lab equipment and the ability to conduct complex characterization on state-of-the-art hardware.
System Engineering Depth: B.Sc/B.Tech in Electrical Engineering, or a related technical field.
Product Development Experience: 5+ years of experience in Product Development, System-Level Debugging, or Architecture. You must understand how a product is designed and manufactured to effectively analyze its failure.
Full-Stack Debugging Skills: Proven ability to troubleshoot issues where the hardware, software, and firmware interface. You are comfortable navigating different technical domains to find a root cause.
Data Fluency: Experience using data analysis tools and a strong interest in applying AI/Machine Learning to automate and scale failure analysis processes.
Leadership Presence: The ability to lead technical teams through high-pressure investigations and clearly communicate findings to both engineering and quality stakeholders.
Ways to Stand Out from the crowd:
Hybrid Technical Background: Experience in Board Design combined with SW or Firmware development.
NPI to Mass Production Expertise: A track record of solving technical problems during the transition from prototype to high-volume manufacturing.
Data Tooling: Experience building custom Python scripts or SQL dashboards to visualize and analyze global product failure distributions.
Failure Avoidance Mindset: Ability to provide technical feedback to R&D teams based on FA findings to improve the robustness of future products.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you! NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer as we highly value diversity in our current and future employees.
Skills Required
- B.Sc/B.Tech in Electrical Engineering or a related technical field
- 5+ years of experience in Product Development, System-Level Debugging, or Architecture
- Expert-level experience with lab equipment and conducting complex characterization
- Proven ability to troubleshoot issues across hardware, software, and firmware
- Experience using data analysis tools
- Experience in Board Design combined with SW or Firmware development
- Track record of solving problems during transition from prototype to high-volume manufacturing
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
