Deep Learning Performance Architect

We are now looking for a Senior Deep Learning Performance Architect! NVIDIA is seeking outstanding Performance Analysis Architects to help analyze and develop the next generation of architectures that accelerate AI and high-performance computing applications.

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. NVIDIA's GPUs run AI algorithms, simulating human intelligence, and act as the brains of computers, robots and self-driving cars that can perceive and understand the world. Increasingly known as “the AI computing company”, NVIDIA wants you. Come, join our Deep Learning Architecture team, where you can help build real-time, cost-effective computing platforms driving our success in this exciting and rapidly growing field!

What you’ll be doing:

• Develop innovative architectures to extend the state of the art in deep learning performance and efficiency

• Prototype key deep learning and data analytics algorithms and applications

• 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

• 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

• 3+ years of relevant work experience

• Strong background in computer architecture and deep learning

• Expert programming skills in Python, C, C++

• Experience with performance and power modeling, architecture simulation, profiling, and analysis

Ways to stand out from the crowd:

• Background in large scale distributed systems architectures and / or a background with GPU Computing and parallel programming models such as CUDA

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

• Experience with the architecture of or workload analysis on other DL accelerators

The base salary range is 148,000 USD - 287,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.