Machine Learning Software Engineering Intern

Cadence has a 25 year history of applying leading edge optimization and analysis algorithms to extremely complex problems in semiconductor and electronic design, verification, and analysis. With its MMSIM platform, Cadence is the market leader in providing circuit simulation tools to thousands of customers, for analog simulation during design and sign-off of a large spectrum of microchips, including the most complex architectures on the most advanced technology nodes (7nm and below).

The Cadence Simulation/MMSIM team is forming a team to explore applications of Deep and Machine Learning techniques to analog circuit simulation and characterization. You will collaborate with our team to define your research project, investigate techniques and tools, and work towards working prototypes. Join us to drive research in this exciting area.

Requirements:

• A full-time student pursuing a MS/PhD in some combination of machine learning, data science, computer science, or engineering
• Experience with software development in C/C++ and Python
• Experience with existing Deep Learning Frameworks such as Tensorflow, Caffe, Theano, Torch, etc.
• Some familiarity with fundamental machine learning techniques such as classification, regression, clustering
• Some basic experience in Electrical Engineering, circuit design, and application of related EDA tools.