Senior Deep Learning Performance Architect

Job Description

NVIDIA is seeking a Senior Deep Learning Performance Architect to help analyze and develop the next generation of architectures that accelerate AI and high-performance computing applications.

Requirements

• 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++

Responsibilities

• 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

Benefits

• Multiple relocation packages
• Two weeklong shutdowns (mid-summer and year-end) in the US (in addition to PTO)
• 8-week parental leave
• 9 Employee Resource Groups
• Annual bonus offering
• Flexible work arrangements
• Up to 6% 401K matching