At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.
Member of the Tensilica Neural Network Compiler Software team within Cadence responsible for developing neural network compiler software and applications that enable customers efficiently deploy neural networks on our DSP and other hardware platforms.
Develops software using C++ to implement neural network processing. Accelerates neural network inference on CPU and GPU targets using techniques such as compression, pruning, quantization and other algorithmic and functional transformations.
Plans and executes projects and mentors other team members
Keeps up to date with developments in the neural network field
The Position Requirements are
Master of Science or PhD in Computer Science, Electronics engineering or related field
Relevant academic or industry experience
Strong C++ programming skills in windows (Visual Studio) or Linux environments
Experience with optimizing computer vision, image processing or neural network inference for embedded systems using techniques like quantization, vectorization, parallel processing, etc.
Familiarity with Neural Network Inference Optimization techniques like Quantization Aware Training, Post training quantization and network pruning preferred
Experience developing complex software in C++ such as for machine learning, computer vision, Image processing, etc. with particular emphasis on fixed point processing.
Experience developing machine learning and neural network applications using popular frameworks such as Tensorflow, Tensorflow Lite, Pytorch, TensorRT, etc. preferred
Knowledge of machine learning compilers like TVM or GLOW preferred
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