Deep Learning Kernel Software Performance Architect - New College Grad 2026

NVIDIA • Santa Clara, CA

8d

About The Position

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are looking for a Performance Architect for Deep Learning Software! NVIDIA is seeking extraordinary architects to develop processor and system architectures that accelerate machine learning, data analytics and high-performance computing applications. This position offers the chance to create a relevant impact in a dynamic, technology-focused company.

Requirements

• Master's or PhD in Computer Science, Electrical Engineering or Computer Engineering, or equivalent experience.
• Proven expertise in software design, including debugging, performance analysis, and test development
• Hands-on experience with practical parallel programming, even if it’s not on GPUs.
• Strong understanding of computer architecture, with practical experience on performance debugging.
• Ability to identify bottlenecks, optimize resource utilization, and enhance system throughput
• Fluency in programming languages such as Python, C, C++.

Nice To Haves

• Strong foundation in machine learning and deep learning fundamentals to complement your expertise in computer architecture.
• A strong background in high performance power efficient designs, energy efficient high-performance computing, performance analysis and profiling to identify performance bottlenecks.
• Experience and familiarity with GPU computing and parallel programming models.
• Work experience with analytical performance modeling, profiling, and analysis

Responsibilities

• Validate and analyze performance of GPU-accelerated system and software architectures that advance the frontier of deep learning performance.
• Debug deep learning and data analytics software to identify root causes of performance bottlenecks.
• Develop scripts and tools to analyze, visualize, and debug software using analytical models, simulators, and test suites
• Collaborate across NVIDIA teams: Work with the CUDA and AI Compiler teams to pinpoint and resolve performance issues
• Engage AI/ML training and inference performance teams to identify and optimize critical deep learning layers
• Collaborate with hardware architecture performance teams to define expectations for emerging deep learning hardware features

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Number of Employees: 5,001-10,000 employees