Senior Research Scientist, Design Automation (EDA)(AI)

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. What you will be doing: NVIDIA Design Automation research group is seeking research scientists in the areas of AI for chip design and GPU accelerated EDA. Deep learning and GPU advancement are changing the landscape of chip design. In this position, you will conduct original research across broad technical areas including EDA algorithms and software, machine learning, and VLSI chip design methodology. Specific areas of research interest include but are not limited to applications of supervised learning, unsupervised learning, reinforcement learning and GPU acceleration to EDA algorithms. - Apply deep learning 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: - PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field. - Strong publication record in leading EDA or ML conferences on DL for EDA or GPU accelerated EDA. - Strong knowledge in one or more EDA/VLSI fields and deep learning - Excellent programming skills in two of Python/PyTorch/C++/CUDA. - Ability to work independently. Ways to stand out from the crowd: - Publishing record on top AI conferences - High impact open-source tools developer - Strong communication skills. Creative and dynamic presenter.