Deep Learning Performance Architect

Overview

• NVIDIA has continuously reinvented itself.
• Our invention of the GPU sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing.
• Today, research in artificial intelligence is booming worldwide, which calls for highly scalable and massively parallel computation horsepower that NVIDIA GPUs excel.
• NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world.
• This is our life’s work , to amplify human creativity and intelligence.
• As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.
• Come join our diverse team and see how you can make a lasting impact on the world! 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 HW architectures to extend the state of the art in parallel computing performance and energy efficiency.
• Benchmark and analyze AI workloads in single and multi-node configurations.
• Develop tools to profile, analyze and debug parallel applications in Python/C++.
• Work closely with peer architecture teams and product management to guide development of the products.
• Keep abreast with emerging trends and research in deep learning.
• What we need to see: B.Tech.
• in a relevant discipline (CS, EE, Math).
• 1+ years of experience in C, C++ and Python.
• Curious mindset with excellent problem-solving skills.
• Ways To Stand Out From The Crowd: Familiarity with GPU computing and parallel programming.
• Understanding of modern transformer-based model architectures.
• Experience with architecture simulator development, performance modeling, profiling, and analysis.