CAD Engineer - SOC Design Methodology

Reposted 12 Days Ago
Be an Early Applicant
2 Locations
In-Office
136K-219K Annually
Mid level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Develop and maintain system-level SOC design methodology and top-level assembly tools in C++. Build APIs, libraries, and command-line tools; create automated test/CI infrastructure; identify and fix assembly inefficiencies; collaborate across teams to standardize workflows; support RTL integration and deliver high-quality automation and documentation for SOC assembly.
Summary Generated by Built In

NVIDIA is looking for a CAD Engineer to join our SOC Design Methodology team! At NVIDIA, you'll collaborate with brilliant minds to build cutting-edge GPUs and SOCs that power everything from AI to gaming! As a Software Engineer, SOC Design Methodology, you'll work at the forefront of technology, integrating advanced ASICs, and partnering with experts in ASIC design, Physical design, CAD, Package Design, Software, DFT, and more. Our ASICs pack hundreds of billions of transistors—pushing the boundaries of performance and sustainability. If you're passionate about automation, efficiency, and making a real impact, NVIDIA SOC Design team is the place to amplify your creativity and accelerate your career.

From pioneering the GPU in 1999—sparking the PC gaming revolution and redefining computer graphics—to leading the charge in AI and deep learning, we are always pushing boundaries." We're a "learning machine," constantly evolving to solve new challenges and seize opportunities that make a real difference. If you're driven by innovation and want to be part of a team that's shaping the future, NVIDIA is where your impact will be felt!

What you’ll be doing:

  • Develop, refine, and maintain system-level methodologies and software tools for efficient SOC creation, with a primary focus on top-level assembly tools and flows written in C++

  • Design, implement, and test robust software components (APIs, libraries, command-line tools) to streamline SOC design and assembly through innovative integration efforts

  • Build and improve automated test infrastructure (unit/regression) to ensure correctness, scalability, and long-term maintainability of SOC assembly workflows

  • Spot inefficiencies in the SOC/front-end implementation and assembly process and propose actionable improvements (tooling, workflow, usability, performance)

  • Collaborate across teams to drive standard methodologies and continuous improvement in SOC development, including requirements gathering, documentation, and user support

  • Enable high-quality RTL and integration collateral delivery to downstream teams with thorough quality checks, automation, and reviews

  • Occasionally use the top-level assembly tools/flows for IP integration and SOC assembly tasks, helping validate and improve methodology in real projects

  • Contribute scripting and infrastructure improvements (e.g., automation, CI, build systems, environment setup) to accelerate methodology adoption

What we need to see:

  • BS or MS in Computer Engineering, Computer Science, Software Engineering, Electrical Engineering, or equivalent experience

  • 3+ years of hands-on software engineering experience, ideally developing C++ tools used in design/automation or other large-scale engineering workflows

  • Strong analytical and problem-solving skills, with a focus on debugging complex systems and improving reliability/performance

  • Strong C++ programming skills, including design for maintainability, code reviews, testing, and performance awareness

  • Proficiency in Python, Perl, or similar scripting languages for automation and workflow improvements

  • Working knowledge of SOC integration concepts and RTL-to-implementation flows (e.g., synthesis, place and route, timing/quality checks) is a plus

  • Excellent communication and teamwork abilities to build consensus within and across teams, translating user needs into effective tools and processes

Ways to stand out from the crowd:

  • Led automation/tooling initiatives that significantly boosted efficiency, quality, or usability for large engineering teams

  • Experience building scalable test/regression frameworks and CI for complex C++ and scripting-based toolchains

  • Hands-on familiarity with SOC assembly/integration workflows and industry-standard EDA tools/flows, especially for large-scale SOC integration

  • Experience mentoring junior engineers or leading cross-functional technical projects

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. Are you creative and autonomous? Do you love the challenge of crafting the most sophisticated chips in the world? If so, we want to hear from you.

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until March 1, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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 or MS in Computer Engineering, Computer Science, Software Engineering, Electrical Engineering, or equivalent experience
  • 3+ years of hands-on software engineering experience (ideally developing C++ tools for design/automation or large-scale engineering workflows)
  • Strong C++ programming skills including maintainable design, code reviews, testing, and performance awareness
  • Proficiency in Python, Perl, or similar scripting languages for automation
  • Strong analytical and problem-solving skills focused on debugging complex systems and improving reliability/performance
  • Excellent communication and teamwork abilities to translate user needs into effective tools and processes
  • Working knowledge of SOC integration concepts and RTL-to-implementation flows (synthesis, place and route, timing/quality checks)
  • Experience building scalable test/regression frameworks and CI for complex C++ and scripting-based toolchains
  • Experience leading automation/tooling initiatives or mentoring junior engineers

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.

  • 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.
  • 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.
  • 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.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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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