NVIDIA is seeking a strong hardware engineer to drive AI adoption for the MSS-Interconnect frontend team. In this role, you will identify where modern AI can create real value for RTL, verification, debug, and design-review workflows, and turn promising capabilities into practical solutions engineers use every day. You will work across global, cross-site RTL, verification, CAD, and methodology teams to improve productivity through trusted, scalable AI workflows.
What you'll be doing:
Identify high-impact opportunities to apply AI across RTL, verification, debug, code understanding, and design-review workflows.
Continuously evaluate new AI tools, models, and agent capabilities, and determine which are worth adopting for real engineering work.
Build and maintain AI-assisted workflows, tools, and reusable components that improve team productivity.
Partner with hardware engineers to turn real pain points into practical AI use cases and iterate based on usage and feedback.
Drive adoption beyond early prototypes by improving workflow quality, reliability, and long-term usefulness.
Help the team make sound decisions on where to experiment, invest, and scale as the AI landscape evolves.
What we need to see:
BS or MS in Electrical Engineering, Computer Engineering, or a related field, or equivalent experience.
3+ years of relevant experience in ASIC / SoC frontend engineering, verification, design methodology, or engineering productivity tooling.
Strong understanding of hardware frontend workflows, including RTL design, verification, debug, and design reviews.
Strong Python and software engineering skills, with experience building practical automation or tools for engineers.
Sufficient hardware depth to judge whether an AI-assisted solution is useful, technically sound, and deployable.
Strong problem-solving, communication, and cross-team collaboration skills.
Ways to stand out from the crowd:
Experience building or deploying LLM-based tools, agents, or AI-assisted workflows for engineering users.
Strong hands-on familiarity with modern AI tooling and good judgment on which new tools are worth trialing or adopting.
Experience driving sustained adoption of internal tools, not just prototypes or isolated evaluations.
Familiarity with frontend hardware development environments and debug-intensive workflows.
Background with Interconnect, NoC, Memory System, bus-fabric, or related silicon domains.
Skills Required
- BS or MS in Electrical Engineering, Computer Engineering, or related field, or equivalent experience.
- 3+ years experience in ASIC / SoC frontend engineering, verification, design methodology, or engineering productivity tooling.
- Strong understanding of hardware frontend workflows including RTL design, verification, debug, and design reviews.
- Strong Python and software engineering skills; experience building practical automation or tools for engineers.
- Sufficient hardware depth to evaluate and judge deployability of AI-assisted solutions.
- Strong problem-solving, communication, and cross-team collaboration skills.
- Experience building or deploying LLM-based tools, agents, or AI-assisted workflows for engineering users.
- Hands-on familiarity with modern AI tooling and judgment on tools worth trialing or adopting.
- Familiarity with frontend hardware development environments and debug-intensive workflows.
- Background with Interconnect, NoC, Memory System, bus-fabric, or related silicon domains.
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.”
