Senior Research Scientist, EDA and AI
NVIDIAJob Title
Senior Research Scientist, EDA and AI
Role Summary
Lead original research at the intersection of Electronic Design Automation (EDA), VLSI design methodology, and machine learning, focusing on GPU-accelerated solutions that translate into production tools and product impact.
Work closely with circuit design, VLSI, and architecture teams and with external researchers to publish, prototype, and deploy research outcomes.
Experience Level
Senior-level. The role expects demonstrated senior research and engineering experience (examples in the posting include 2+ years post-PhD research and multi-year experience applying AI and GPU computing).
Responsibilities
Primary responsibilities include original research, system/prototype development, and cross-functional collaboration to drive impact.
- Define and conduct original research in EDA algorithms, VLSI methodology, and machine learning techniques.
- Design and implement GPU-accelerated optimization and ML methods for large-scale EDA problems.
- Translate research into software tools and products through prototyping and collaboration with product teams.
- Publish and present results at top conferences and engage with the global research community.
- Lead and mentor researchers, and coordinate collaborations with academia and industry partners.
Requirements
Must-have technical and professional qualifications (education details are summarized below in Education Requirements).
- Proven research record with impactful publications in EDA and AI/ML venues.
- Deep domain knowledge in EDA/VLSI topics such as synthesis, formal verification, timing, reliability, or physical design algorithms.
- Extensive experience applying AI techniques (supervised, unsupervised, reinforcement learning) to real problems and using GPU/accelerator-based computing.
- Strong software development skills and experience in high-performance computing, parallelism, and large-scale software engineering.
- Experience leading projects or teams and mentoring junior scientists; proven cross-functional collaboration with circuits/VLSI/architecture teams.
- Excellent written and verbal communication; demonstrated ability to present at top conferences and influence technical and non-technical stakeholders.
- Track record of releasing high-impact open-source tools, datasets, or frameworks is highly valued.
Education Requirements
PhD in Computer Science, Electrical/Computer Engineering, or a related technical field, or equivalent practical experience. The posting indicates an expectation of ~2+ years of post-PhD research experience (or equivalent research experience) and substantial applied experience in AI and GPU/accelerated computing.
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.
