NVIDIA is actively searching for talented Senior Verification Engineers to ensure the integrity and excellence of our industry-leading SoCs and GPUs. Joining this team means stepping into a dynamic, innovation-driven environment where your contributions will shape products spanning consumer graphics, autonomous vehicles, and the rapidly evolving realm of artificial intelligence. Our global team is dedicated to redefining the boundaries of technology, working collaboratively to advance what's possible today and set the foundation for tomorrow's computing platforms. We are a team of hardworking engineers working across the micro-architecture, design, verification, implementation, and post silicon validation of groundbreaking NVIDIA automotive and gaming console chips. We specifically focus on the backbone IPs for an ARM based System on-chip.
What You’ll Be Doing:
As a key member of our ASIC Verification team, you will verify the design and implementation of the industry's leading SoCs, ensuring first-pass silicon success.
Lead the verification of the ASIC design, architecture, golden models, and micro-architecture using sophisticated methodologies such as UVM.
Deeply understand the design, define the verification scope, and develop robust verification infrastructure to verify the correctness of complex logic.
Collaborate with architects, designers, and both pre- and post-silicon verification teams to drive comprehensive coverage.
Innovate by bringing AI and LLM-driven workflows into the verification cycle to optimize testbench generation, debug productivity, and coverage closure.
What We Need to See:
BS or equivalent experience in Electrical Engineering, Computer Engineering, or Computer Science; advanced degrees (MS, PhD) are a plus.
5+ years of experience in ASIC verification-related fields at both the IP and SoC level.
Proven experience in building UVM testbenches from scratch and applying constrained random methodology in a production environment.
High proficiency in C/C++ with the ability to develop architectural golden models and hardware-software co-verification tests.
Deep domain knowledge in Low-Speed IOs (QSPI, UART, I2C), High-Speed IOs (Ethernet), AXI/APB interconnects, DMA controllers, and Memory Controllers.
Expert skills in assertion-based design checks (SVA), code coverage, functional coverage, and formal test plan documentation.
Strong debugging and analytical skills with a methodical approach to resolving complex SoC-level corner cases.
Professional-grade scripting abilities in Python, Perl, or TCL to automate build flows and regressions.
Ways to Stand Out from the Crowd:
Advanced UVM architecture knowledge and large-scale SoC verification experience is a plus!
A forward-thinking mindset with a demonstrated ability to use AI tools to accelerate engineering tasks.
Experience with Testbench Build flows, Makefiles, and version control (Perforce).
Ambitious, highly motivated, and a strong desire to work as a collaborative teammate in a fast-paced environment.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- BS degree or equivalent experience in Electrical Engineering, Computer Engineering, or Computer Science
- 5+ years of experience in ASIC verification-related fields at both IP and SoC level
- Experience building UVM testbenches from scratch
- Production experience applying constrained-random methodology
- High proficiency in C/C++
- Experience developing architectural golden models and hardware-software co-verification tests
- Deep knowledge of low-speed I/O protocols including QSPI, UART, and I2C
- Deep knowledge of high-speed I/O, including Ethernet
- Knowledge of AXI/APB interconnects, DMA controllers, and memory controllers
- Expertise in assertion-based design checks, code coverage, functional coverage, and formal test plan documentation
- Strong debugging and analytical skills for complex SoC-level corner cases
- Professional-grade scripting ability in Python, Perl, or Tcl
- Advanced degree such as MS or PhD
- Advanced UVM architecture knowledge and large-scale SoC verification experience
- Experience using AI tools to accelerate engineering tasks
- Experience with testbench build flows, Makefiles, and Perforce
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.”
