Are you someone who thrives when tackling the most intriguing challenges in computer architecture for deep learning? Do you find yourself energized by bridging the worlds of hardware and software? If so, NVIDIA is searching for innovative performance architects who are passionate about maximizing every ounce of performance from deep learning codes.

We’re looking for a talented individual to conduct in-depth performance analysis and develop kernels for NVIDIA’s latest architectures. Your contributions will be pivotal in advancing the hardware and software that power next-generation AI applications, ensuring they achieve optimal performance. This is a unique chance to make a substantial impact within a dynamic, technology-driven company.

What you'll be doing:

• Analyze the performance of a wide range of machine learning and deep learning algorithms across existing and emerging architectures.

• Identify bottlenecks and devise creative software solutions or recommend improvements in GPU architectures.

• Explore and evaluate how hardware and software architectures interact with future algorithms and applications.

What we need to see:

• An MS or PhD in a relevant field like Computer Science, Electrical Engineering, or Mathematics.

• At least 3 years of professional experience with performance modeling, analysis, and code optimization for deep learning operators on GPU, CPU, or LPU—including hands-on assembly or SIMD programming.

• Solid foundation in computer architecture.

• Proficiency in programming languages such as C, C++, Perl, or Python.

Ways to stand out from the crowd:

• You’re knowledgeable about LLM frameworks and their fundamentals.

• Experience with parallel programming and CUDA or OpenCL.

• You have modeled GPU/CPU Core Engine or Mem System architectures.

• Possess strong communication and organizational skills.

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) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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