Applied AI Engineer - VLSI Design
NVIDIAJob Title
Applied AI Engineer - VLSI Design
Role Summary
Work on AI-driven tools for VLSI memory and chip design, developing agentic applications and infrastructure that integrate machine learning with CAD flows to accelerate circuit implementation and closure.
The role sits on NVIDIA's custom RAM design team and combines software engineering, machine learning, and VLSI domain collaboration to deliver production-quality engineering assistants and data-driven design tooling.
Experience Level
Mid-level — typically 5+ years of relevant industry experience.
Responsibilities
Key responsibilities include designing, building, and deploying AI-based tools and the infrastructure required to integrate them into VLSI design flows.
- Design, prototype, and deploy AI applications using large language models and agentic frameworks for engineering assistants and multi-turn, multi-modal dialogue systems.
- Build infrastructure to deploy LLM-powered solutions and integrate them with CAD flows and engineering toolchains.
- Develop multi-agent solutions, fine-tune models, and implement retrieval-augmented generation pipelines and vector DB integrations.
- Create and maintain design databases, dashboards, and retrieval mechanisms to surface engineering data for faster circuit closure.
- Collaborate across circuit design, layout, technology, and third-party EDA vendor teams distributed across locations and time zones.
Requirements
Must-have technical skills and professional attributes.
- Minimum 5 years of industry experience in software, AI, or related engineering roles.
- Proficiency in rapid prototyping with Python and strong software engineering fundamentals (data structures, algorithms, testing).
- Hands-on experience fine-tuning large language models, building multi-agent systems, and implementing RAG pipelines with vector databases.
- Familiarity with version control, automated testing, and CI/CD practices.
- Strong analytical, communication, and interpersonal skills; ability to work in distributed, product-focused teams.
- Proactive problem-solving attitude and willingness to learn new tools and domains.
Nice-to-have:
- Prior circuit or hardware design experience.
- Experience with multi-modal AI systems or advanced model deployment at scale.
Education Requirements
Master's or PhD in Electrical Engineering, Computer Science or Computer Engineering is preferred — or equivalent practical experience.
About the Company
Company: NVIDIA
Headquarters: Santa Clara, California, USA
NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.
