Senior Research Scientist, EDA and AI

NVIDIA•Santa Clara, CA

About The Position

NVIDIA is seeking a Senior Research Scientist to conduct research at the intersection of AI, GPU computing, and Electronic Design Automation (EDA). The role focuses on advancing chip design through AI and GPU acceleration, developing research into practical tools and products, and collaborating across research and product groups. The position also engages with the research community through publications, presentations, and external collaborations.

Requirements

PhD in Computer Science, Electrical or Computer Engineering, or a related field, or equivalent experience.
At least 2 years of post-PhD research experience.
Strong record of impactful publications in top EDA and AI/ML venues.
Demonstrated ability to set research direction and translate ideas into tools or products.
Deep knowledge of EDA/VLSI, such as synthesis, formal verification, timing, reliability, or physical design algorithms.
At least 5 years applying AI techniques, including supervised learning, unsupervised learning, or reinforcement learning, and GPU/accelerator-based computing to large-scale problems.
At least 5 years of software development experience.
Strong expertise in high-performance computing, parallelism, optimization, and large-scale software engineering.
Experience leading research projects or teams and mentoring junior scientists.
Experience driving cross-functional initiatives with circuits, VLSI, or architecture groups and fostering collaborations with academia or industry.
Excellent written and verbal communication skills, including experience presenting at top conferences.
Ability to influence technical and non-technical audiences.

Responsibilities

Define and conduct original research across EDA algorithms, VLSI design methodology, and advanced machine learning techniques.
Innovate in EDA software and algorithms, including supervised, unsupervised, and reinforcement learning and GPU-accelerated optimization methods.
Collaborate with circuit design, VLSI, and architecture teams to translate research into real-world product impact.
Publish research in premier conferences, present at leading venues, and contribute thought leadership.
Foster collaboration with external researchers and internal product teams.
Lead research projects or teams, mentor junior scientists, and drive cross-functional initiatives.
Develop or release high-impact open-source tools, datasets, or frameworks.