NVIDIA System-On-Chip (SOC) group is hiring for an ASIC Design Engineer! The complexity of the chips we build has increased manifold over the years. We are now packing tens of billions of transistors in a chip to meet the growing computing demand. We are looking for a top ASIC Design Engineer to join our team. In this role, you should have real passion for RTL design implementation and methodologies that enable high quality system-level IP design.
What you'll be doing:
- Be an integral part of the team defining and developing system-level RTL and methodologies to measure performance on the industry's leading GPUs/SOCs.
- Design and implement RTL features - work through the entire design cycle for SOC.
- Run and debug RTL checks to ensure design quality (e.g. CDC, RDC, Lint, Synthesis, Logic-Equivalence and more)
- Define, develop, and automate flows and methodologies to efficiently build and support a system-level IP
- Work with architects, designers, verification and SW engineers to accomplish your tasks.
What we need to see:
- B.Tech or M.Tech in Electronics or Computer Engineering.
- 3+ years of relevant industry experience.
- Experienced in RTL design (Verilog), System-On-Chip design/implementation flows, and design automation.
- Good understanding of SOC/IP (u)architecture (e.g., data flow, control, multiple clock/power domains handling, latency analysis).
- Strong coding skills in Perl, Python or other industry-standard scripting languages.
- Excellent debugging and analytical skills.
- Exposure to design and verification tools (dc_shell or equivalent synthesis tools, VCS or equivalent simulation tools, debug tools like Debussy, GDB).
- Great communication and collaboration skills to interact within the team and with cross functional teams.
- Adept at using AI tools to enhance productivity and solve complicated problems
NVIDIA is widely considered one of the technology world’s most desirable employers. We employ some of the most forward-thinking and innovative people in the world. Are you passionate about joining our life’s work to amplify human imagination and intelligence? If you are creative, collaborative, and have real passion for design, methodology, and automation, we want to hear from you!
#LI-Hybrid
Skills Required
- B.Tech or M.Tech degree in Electronics or Computer Engineering
- 3+ years of relevant industry experience
- Experience with RTL design using Verilog
- Experience with SoC design and implementation flows
- Experience with design automation
- Understanding of SoC/IP microarchitecture, including data flow, control, clock and power domains, and latency analysis
- Strong coding skills in Perl, Python, or other industry-standard scripting languages
- Excellent debugging and analytical skills
- Exposure to synthesis, simulation, and debug tools such as dc_shell, VCS, Debussy, or GDB
- Strong communication and collaboration skills
- Ability to use AI tools to improve productivity and solve complex problems
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.”
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