Senior Deep Learning Performance Architect

Job Description

NVIDIA is seeking a Senior Deep Learning Performance Architect to help develop innovative HW architectures for AI acceleration and high-performance computing applications.

Requirements

• MS or PhD in a relevant discipline (Computer Science, Electrical Engineering, Computer Engineering, etc) or equivalent experience.
• 4+ years of experience in parallel computing architectures, interconnect fabrics, and deep learning applications.
• Background in GPU or Deep Learning ASIC architecture evaluation for training and/or inference.
• Strong programming skills in Python and C++.

Responsibilities

• Develop innovative HW architectures to extend parallel computing performance, energy efficiency, and programmability.
• Benchmark and analyze AI workloads in single and multi-node configurations.
• Develop high-level simulator and analysis tools in C++/Python.
• Evaluate performance, power, area (PPA) for hardware features and system-level architectural trade-offs.
• Work closely with peer architecture teams and product management to guide product development.
• Keep abreast with emerging trends and research in deep learning.

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