NVIDIA is at the forefront of AI-driven innovation in VLSI design automation. Join us to shape the future of semiconductor design with cutting-edge AI tools and make a significant impact in a collaborative, high-performance environment. Are you ready to push the boundaries of what’s possible in VLSI CAD? Come be part of our pioneering team!
What you'll be doing:
- You will be responsible for developing and integrating advanced CAD solutions and automation flows using AI and machine learning for VLSI design, verification, and implementation.
- Work closely with design, verification, and CAD teams to identify areas for improving VLSI workflows using advanced tools and methods.
- Research, prototype, and deploy AI-based algorithms.
- Develop and maintain scripts and automation infrastructure to enable seamless adoption of AI tools in the VLSI design process.
- Continuously review emerging AI technologies and methodologies to keep our CAD environment up-to-date.
- Provide technical support and training to engineering teams on AI-enabled CAD flows and best practices.
What we need to see:
- B.Sc./M.Sc. in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
- 5+ years of experience in VLSI CAD tool development, with a strong focus on integrating AI/ML techniques into EDA workflows.
- Proficiency in Python and at least one AI/ML framework (such as TensorFlow, PyTorch, or scikit-learn).
- Hands-on experience with VLSI physical design and familiarity with industry-standard EDA tools (e.g., Synopsys, Cadence).
- Knowledge of data preprocessing, feature engineering, and model deployment as applied to VLSI design challenges.
- Experience developing and maintaining automation scripts (Python, Perl, Tcl, Make).
- Strong analytical skills in evaluating the impact of AI solutions on design quality, performance, and productivity.
- Excellent communication skills and the ability to work cross-functionally in a fast-paced environment.
- Self-motivation, attention to detail, and a track record of delivering robust solutions to production.
Ways to stand out from the crowd:
- Demonstrated experience deploying AI/ML models in production VLSI CAD environments.
- Contributions to open-source AI/EDA projects or publications in relevant conferences/journals.
- Deep understanding of VLSI design challenges-such as timing closure, power optimization, or yield enhancement-and how AI can address them.
- Experience with cloud-based or distributed compute environments for large-scale AI training and inference.
- Strong ownership, curiosity, and a passion for continuous learning and innovation.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Skills Required
- B.Sc./M.Sc. in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience
- 5+ years of experience in VLSI CAD tool development with focus on integrating AI/ML into EDA workflows
- Proficiency in Python
- Experience with at least one AI/ML framework (TensorFlow, PyTorch, or scikit-learn)
- Hands-on experience with VLSI physical design and familiarity with industry-standard EDA tools (e.g., Synopsys, Cadence)
- Knowledge of data preprocessing, feature engineering, and model deployment applied to VLSI challenges
- Experience developing and maintaining automation scripts (Python, Perl, Tcl, Make)
- Strong analytical skills to evaluate impact of AI solutions on design quality, performance, and productivity
- Excellent communication skills and ability to work cross-functionally
- Self-motivation, attention to detail, and track record of delivering robust production solutions
- Demonstrated experience deploying AI/ML models in production VLSI CAD environments
- Contributions to open-source AI/EDA projects or publications in relevant conferences/journals
- Deep understanding of VLSI challenges (timing closure, power optimization, yield) and AI applications to them
- Experience with cloud-based or distributed compute environments for large-scale AI training and inference
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.
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.”
