Used Tools & Technologies
GPURequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Security @ 7
Linux @ 7
Python @ 8
Distributed Systems @ 6
Leadership @ 4
Networking @ 4
Stress Testing @ 4
Technical Leadership @ 4
AI @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. The company is tapping into the unlimited potential of AI to define the next era of computing. The Data Center MODS organization seeks a Principal Engineer to architect and scale next-generation L10 and L11 diagnostic systems for Cloud Service Providers (CSPs). In this high-impact role, you will define the technical roadmap and lead multi-functional development to deploy robust diagnostic frameworks for AI accelerator products. Proficiency in distributed systems and hardware/software interfaces is essential for success.
Responsibilities
- Define technical strategy and develop NVIDIA’s Data Center diagnostic systems, orchestrating large-scale stress testing for CPUs, GPUs, networking, memory, and high-speed interconnects.
- Mentor and grow engineering teams, providing technical leadership and encouraging a culture of innovation and excellence.
- Drive root-cause analysis of systemic failures that intersect multiple hardware and software domains.
- Partner with Cloud Service Providers (CSPs) to diagnose and address scalability challenges within their unique data center infrastructures.
Requirements
- Bachelor’s degree in Computer Science/Engineering, Electrical Engineering, or a related field (or equivalent experience).
- 15+ years of system software experience working on highly resilient distributed systems with programming experience in C++ or Python.
- Deep systems knowledge of x86 and ARM architectures, Linux OS internals, firmware (UEFI/BIOS), Redfish, HMC, BMC protocols, and platform security.
- Consistent track record demonstrating technical leadership: leading project teams and setting technical direction.
- Expertise in software testing methodologies with an automation-led, AI-first approach to ensuring software quality.
Benefits & Additional Information
- Base salary range: 272,000 USD - 431,250 USD (determined based on location, experience, and comparable roles).
- Eligible for equity and company benefits.
- Applications accepted at least until March 10, 2026.
- NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer committed to diversity and inclusion.