Senior Research Scientist, EDA and AI
$192k - $357k • US, CA, Santa Clara
Posted 2d ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
On-site
Categories
AI Research Engineer
About the job
NVIDIA is seeking a Senior Research Scientist to conduct groundbreaking research at the intersection of AI, GPU computing, and Electronic Design Automation (EDA). This role offers the opportunity to shape the future of chip design through AI and GPU acceleration. You will define and conduct original research across EDA algorithms, VLSI design methodology, and advanced machine learning techniques, innovating in EDA software and algorithms with applications spanning supervised, unsupervised, and reinforcement learning, as well as GPU-accelerated optimization methods. Collaboration with cross-functional teams, the global research community through publications and presentations, and external researchers will be key to translating research into real-world product impact and driving thought leadership.
Responsibilities
- Define and conduct original research in EDA algorithms, VLSI design methodology, and machine learning.
- Innovate in EDA software and algorithms using supervised, unsupervised, and reinforcement learning.
- Apply GPU-accelerated optimization methods to large-scale problems.
- Collaborate with circuit design, VLSI, and architecture teams to ensure research translates to product impact.
- Publish research in premier conferences and present at leading venues.
- Foster collaboration with external researchers and internal product teams.
- Lead research projects and mentor junior scientists.
- Drive cross-functional initiatives and foster collaborations with academia or industry.
Requirements
- PhD in Computer Science, Electrical/Computer Engineering, or related field (or equivalent experience).
- 2+ years of post-PhD research experience.
- Strong record of impactful publications in top EDA and AI/ML venues.
- Proven ability to set research direction and translate ideas into tools or products.
- Deep knowledge in EDA/VLSI (e.g., synthesis, formal verification, timing, reliability, or physical design algorithms).
- 5+ years applying AI techniques (supervised, unsupervised, RL) and GPU/accelerator-based computing to large-scale problems.
- 5+ years of experience in software development.
- Strong expertise in high-performance computing, parallelism, optimization, and large-scale software engineering.
- Experience in leading research projects or teams.
- Track record of mentoring junior scientists.
- Excellent written and verbal communication skills.
- Demonstrated experience presenting at top conferences.
- Track record of releasing high-impact open-source tools, datasets, or frameworks.
- Ability to influence both technical and non-technical audiences.
Benefits
- Equity
- Benefits