Scientific Computing Engineer

3 weeks ago


San Jose, United States Cadence Design Systems, Inc. Full time

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

Cadence Design Systems is a world leader in providing computational software for all aspects of intelligent system design. You will be part of a cross-disciplinary R&D team working on the emerging boundary of scientific computing and machine learning/AI, with specific emphasis in the analog electronic circuit analysis area. The candidate should have an advanced degree in computer science / electrical engineering and the following preferred skills:

4+ years experience in software design/development/deployment with application in ML or other data-intensive applications.

Demonstrated programming proficiency in Python and C++.

Experience and demonstrated proficiency with machine learning frameworks such as PyTorch, TensorFlow, Keras.

Strong computer science background is a plus.

Working knowledge of contemporary methods in deep learning/AI (LLMs, graph neural networks, transformer architectures, CNNs, reinforcement and transfer learning, etc.).

Demonstrated ability to reduce algorithms and theoretical knowledge to practice.

Exposure to physics-informed machine learning algorithms e.g. physics-informed neural networks, neural operator methods, is a plus.

Exposure to one or more application areas in scientific computing (computational electromagnetics, fluid dynamics, molecular dynamics, thermal analysis, electrical circuit simulation) is a plus.

Candidate should expect to work with a cross-functional engineering team to perform cutting-edge research but ultimately deliver innovative technologies in a production environment.

We’re doing work that matters. Help us solve what others can’t.



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