Research Scientist, Design Automation

We are now looking for a Research Scientist – Design Automation!

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and build our teams with the smartest people in the world. Would you like to join us at the forefront of technological advancement?

NVIDIA Design Automation research group is seeking leading researchers to work on AI for chip design and accelerated computing for EDA. You should have a strong track record of research excellence; systems-building experience; a broad perspective across areas including EDA algorithms and software, machine learning (Graph, Generative AI, LLM, Agent) , and VLSI chip design methodology. Specific areas of research interest include but are not limited to applications of supervised learning, unsupervised learning, reinforcement learning , generative AI, LLM, Agent and GPU acceleration to EDA algorithms.

What you’ll be doing:

• Apply machine learning (Graph, Generative AI, LLM, Agent) and GPU acceleration to EDA software and ASIC and VLSI design tool flows.

•  Research and develop creative and innovative EDA software and algorithms.

• Collaborate with circuits, VLSI, and architecture team members in research and product teams.

• Publish and present your original research, speak at conferences and events

• Collaborate with external researchers and a diverse set of internal product teams.

What we need to see:

• Pursuing Ph.D in EE or related with a strong research record, well-referenced publications and / or patents (or equivalent experience)

• You should display a strong background in EDA algorithms and software development, machine learning, along with knowledge of VLSI, circuits, IC design, and/or computer micro-architecture fundamentals.

• Experience with C, C++, Python, and scripting languages.

• Background with commonly used machine learning frameworks (PyTorch, Tensorflow).

• Experience with CUDA and GPU computing

• Strong communication skills needed. Being a creative and dynamic presenter is a huge advantage.

With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for computer architecture and technology, we want to hear from you!