Applied AI Engineer - VLSI Design
Agentic Ai
Ai Automation
Ai Ml
Analytics
Artificial Intelligence
Data Analysis
Data Analytics
Data Architecture
Data Integration
Data Pipeline
Data Platform
Design Automation
Design Engineering
Electrical Design
Engineering
Hardware Engineering
Hardware Software Co Design
Programming
Programming Language
Programming Languages
Job Description
Applied AI Engineer focusing on VLSI design at NVIDIA, delivering AI powered tooling to support VLSI engineering flows and CAD systems in a hybrid Santa Clara, CA setting.
Responsibilities
- Lead design, development, and deployment of AI applications using LLMs, internal and external Agentic frameworks, and related technologies to support VLSI engineering workflows.
- Architect and implement the infrastructure required to deploy LLM powered engineering assistants and multi turn, multi modal dialogue systems.
- Develop agentic AI solutions to tackle complex VLSI design challenges, integrating and fine tuning them with CAD flow systems.
- Apply AI techniques to improve efficiency in chip design processes and problem solving.
- Build and maintain design databases and dashboards leveraging agentic and deterministic retrieval to surface relevant engineering data and accelerate design closure.
- Collaborate with circuit design, layout, technology, and third party EDA vendors across geographies and time zones.
Requirements
- Master's or PhD degree in Electrical Engineering or Computer Science/Engineering or equivalent experience.
- 5+ years of proven industry experience in a related field.
- Proficiency in rapid prototyping using Python with strong foundation in data structures, algorithms, and software engineering principles.
- Experience fine tuning large language models, building advanced multi agent systems, RAG pipelines and vector databases.
- Strong analytical, communication, and interpersonal skills, with a track record of thriving in dynamic, product focused, and distributed teams.
- Proactive problem solving and willingness to acquire new skills and knowledge as needed to achieve results.
Technologies
- Python
- Large Language Models (LLMs)
- Agentic frameworks
- RAG pipelines
- Vector databases
- CAD flow systems
Benefits
- Equity
- Benefits package
Ways to stand out
- Experience with Large Language Models (LLMs) and their applications in software and AI development.
- Proficiency in standard software development practices, including version control, testing, and CI/CD.
- Curiosity and ability to learn disparate concepts and combine them in innovative ways.
- Prior experience with circuit design or hardware design is a plus.
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