Senior System Integration and Feature Validation Engineer
NVIDIA · Posted Sep 29
Graphics processing units, artificial intelligence platforms, accelerated computing, and data center solutions
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About the role
NVIDIA's Silicon Co-Design Group owns feature integration, debugging, validation, and productization across all NVIDIA GPU, CPU, Client, and SoC products, covering everything from architecture to bring-up and release. The team works at the boundary between hardware and software — boot, clocks, DVFS, performance and power system controllers, circuits, and silicon bring-up. This senior role carries end-to-end responsibility for cross-stack feature integration and root-cause resolution, builds AI-enabled validation and triage workflows, and partners with globally distributed architecture, ASIC, firmware, driver, and software teams.
What you will do
- End to End responsibility for the integration and product development of system features across — boot, clocks, DVFS, performance and power system controllers, and certain circuits.
- Lead debugging and root-cause resolution on the most challenging cross-stack feature issues covering silicon, firmware, driver, and platform — delivering productized fixes and reusable workarounds.
- Build and deploy AI-enabled workflows for feature validation, debug, and triage — with explicit guardrails and measurable impact on cycle time, coverage, or escape rate.
- Support silicon bring-up, feature deployment, and GPU/SoC qualification through feature checks, PVT stress and stability testing, and lab debug.
- Build the tools, scripts, and infrastructure the team relies on — and improve validation and productization processes for greater quality and efficiency.
- Partner with globally distributed teams — architecture, ASIC, firmware, driver, software, and multiple bring-up teams.
Skills used in this role
What the employer is looking for
- BTech / BE or MTech / ME in Electronics, Electrical, or Computer Engineering along with over 5 years of experience in post-silicon bring-up, system integration, or feature design and validation for released GPU, CPU, or SoC products. At least once, you should have diagnosed a vague, cross-team feature failure and delivered a finalized fix.
- Strong end-to-end understanding of hardware, firmware, and software interaction — with fundamentals in board and system development, DVFS, control loops, SI/PI, timing, clocking, high-speed I/O, PVT, and thermal — and hands-on silicon, board, and lab-debug muscle memory.
- Practical understanding of GPU, CPU, or SoC architectures within at least one of PC, datacenter, or automotive environments — proven experience leading efforts to address unclear issues spanning multiple teams.
- Proven validation approach using smart AI technology you designed or scaled, not only used — with adoption beyond yourself and measurable impact on debug velocity, coverage, or escape rate. You can detail the limits you set and where smart AI tools may introduce hazards in your workflow.
Preferred qualifications
- A history of building reusable feature-integration methodology, debug playbooks, or validation frameworks that other programs or teams adopted. These are backed by patents, conference papers, or talks where you were encouraged to present.
- Practical subsystem expertise in DVFS, boot / clock / reset, power management controllers, high-speed I/O, or thermal — including failure modes, debug instrumentation, and the compromises encountered during production.
- Experience partnering deeply with a counterpart team in another major engineering hub — shared on-call, shared metrics, and shared culture across geographies.
- AI work that goes beyond personal-copilot uses agentic workflows, RAG-grounded debug assistants, machine learning-based anomaly detection, or automated triage — deployed at team scope with adoption metrics.
Benefits and support
- Flexible time off
- Continuous learning
About NVIDIA
NVIDIA Corporation is a multinational technology company that designs graphics processing units (GPUs) for the gaming and professional markets, as well as system on a chip units (SoCs) for the mobile computing and automotive market. Pioneering accelerated computing, the company has become a driving engine of modern artificial intelligence, deep learning, and data center infrastructure.
- Industry
- Semiconductors
- Company size
- 42000+ employees
- Founded
- April 5, 1993
- Location
- Santa Clara, California, USA
- Funding stage
- Public Company
Funding
Public Company · $5M raised
Leadership
Founder, President and Chief Executive Officer
Executive Vice President and Chief Financial Officer
Founder and NVIDIA Fellow
Executive Vice President, Worldwide Field Operations
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