1 day ago
Base Salary
$184k - $288k/yr
Responsibilities
- Develop and maintain diagnostic software suites to stress-test NVIDIA GPUs and SoCs and identify hardware defects, including silent data corruption.
- Analyze diagnostic coverage gaps and improve failure detection, repeatability, and test-time efficiency.
- Model and analyze reliability and availability metrics, including FIT, AVF, and availability from GPU through datacenter scale.
- Analyze field hardware interruption and failure data and improve fault attribution, containment, and recovery models.
- Build automation scripts and tooling to launch, monitor, and manage diagnostic jobs across independent compute clusters.
- Develop dashboards that integrate diverse data sources and provide analytics, visualization, secure access, reliable hosting, and multi-user performance.
- Collaborate with engineering teams to classify cluster failures as hardware faults, test-script bugs, or environment configuration issues.
- Evolve diagnostics and availability models to reflect changing AI workloads.
Requirements
- Master's degree in Computer Engineering, Electrical Engineering, Computer Science, or a closely related field, or equivalent experience.
- At least 5 years of relevant experience.
- Knowledge of GPU architecture, GPU programming, and hardware diagnostics.
- Understanding of reliability and FIT models, AVF estimation, availability concepts, and ECC, parity, and CRC strategies.
- Proficiency in data mining, automation, Python, SQL or similar tools, C/C++, and CUDA programming.
- Strong debugging, analytical, statistical, and judgment skills, including evaluating exposure-adjusted rates and sample sizes.
- Experience with hardware diagnostics and container-based job execution.
- Ability to collaborate effectively with on-site and remote engineering teams.
- Experience with embedded software or visualization and data analytics tools is a plus.
- Understanding of resiliency and reliability trade-offs, failure modes, mitigation, recovery strategies, and AI datacenter workloads is preferred.
Benefits
- Eligible for equity and benefits.
- Applications accepted at least until November 7, 2026.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.