Senior GPU Architect, Deep Learning

Responsibilities

• 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.
• What we need to see
• MS in Computer Science, Electrical Engineering or Computer Engineering or equivalent experience.
• Experience in working with hardware targeted at deep learning, or working on mapping deep learning algorithms to hardware.

Languages