Senior GPU Architect, Deep Learning

Design new hardware features for future processing architectures targeted at deep learning workloads, for both training and inference. Advance the state of parallel computation. Be knowledgeable about future parallel programming models and their impact to hardware. Develop software for various hardware simulators, test infrastructures or metrics systems including databases. Work in a team to document, design, develop tools to analyze and simulate, validate, and verify functional or performance models. Develop tests, testplans, and testing infrastructure for new graphics or parallel processing architectures Be hungry to learn and work on simulators, RTL and real silicon. Experience in working with hardware targeted at deep learning, or working on mapping deep learning algorithms to hardware.