Develop innovative architectures to extend the state of the art in deep learning performance and efficiency
Analyze performance, cost and power trade-offs by developing analytical models, simulators and test suites
Understand and analyze the interplay of hardware and software architectures on future algorithms, programming models and applications
Evaluate PPA (performance, power, area) for hardware features and system level architectural trade-offs.
Develop high level simulators in C++/Python
Actively collaborate with software, product and research teams to guide the direction of deep learning HW and SW

MS or PhD in Computer Science, Computer Engineering, Electrical Engineering or equivalent experience
6+ years of relevant meaningful work experience
Strong background in GPU or Deep Learning ASIC architecture for distributed training and/or inference spanning multi-chip/multi-node
Experience with performance modeling, architecture simulation, profiling, and analysis
Solid foundation in machine learning and deep learning. Understanding of modern transformer-based architectures and their performance at scale.
Strong programming skills in Python, C, C++

Senior Deep Learning Performance Architect

Key skills