Senior Deep Learning Performance Architect

We are now seeking a Senior Deep Learning Performance Architect! As a Senior Deep Learning Performance Architect at NVIDIA, you will help analyze and develop the next generation of architectures that accelerate AI and high-performance computing applications.

Key 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

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++

Nice to Have:

• 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

You will also be eligible for equity and benefits.