Nvidia Senior Deep Learning Performance Architect 

United States, Texas 

404731251

NVIDIA is looking for outstanding Performance Architects with a background in performance analysis, performance modeling, and AI/deep learning to help analyze and develop the next generation of architectures that accelerate AI and high-performance computing applications.

What you’ll be doing:

• 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

What we need to see:

• 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 spanningmulti-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++

Ways to stand out from the crowd:

• Background with deep neural network training, inference and optimization in leading frameworks (e.g. Pytorch, JAX, TensorRT)

• Familiarity with advanced optimizations and SW/HW co-design in LLM training and inference

• Exposure to using AI to accelerate SW engineering

• Demonstration of self-motivation and creative / critical thinking