We are looking for a passionate and energized engineer to accelerate the integration of APIs across the CUDA-X math library software stack into modern LLM and agentic AI workflows. Leading organizations globally are using GPU-powered data centers for AI, data analytics, and scientific simulations, driving advancements in fields like LLMs, computer vision, CAE, EDA, and autonomous vehicles. Our team develops the GPU-accelerated libraries and SDKs essential for these technologies.

In this role, you will be responsible for ensuring both human engineers using LLMs and AI agents alike to build high-performance applications with ease through effective utilization of CUDA-X libraries. Do you have the rare blend of technical, developer experience and communication skills? If so, we would love to learn more about you!

What You'll Be Doing:

• Drive the architecture and implementation of math libraries APIs and documentation structures designed to be LLM-first: introspectable, explainable, and easily synthesized by AI agents.

• Work with internal and external stakeholders to deliver timely LLM-enhanced library releases.

• Build metrics, tools and processes to measure impact and quality of LLM/agentic code generation.

• Prototype tooling and solutions to help transform math libraries’ APIs into LLM-friendly representations across popular codegen tools.
   

What We Need To See:

• PhD or MSc’s degree in Computational Science, Computer Science, Applied Math, or related science or engineering field of study is preferred (or equivalent experience)

• 3+ years of experience

• Robust knowledge of LLMs, finetuning, RL, building RAGs, MCP, and building agenting tooling

• Proven experience designing clear, composable APIs and writing high-quality, well-documented code for complex technical domains

• Ability to prioritize multiple projects and work independently with minimal direction

• Excellent collaboration, communication, and documentation habits
   

Ways To Stand Out From The Crowd:

• Prior work in AI-assisted software engineering, code generation, or programming language design

• Familiarity with CUDA-X math library APIs: cuBLAS, cuFFT, cuSOLVER, cuSPARSE, etc.
   

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing for science and engineering. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and build our teams with the smartest people in the world! Join us at the forefront of technological advancement. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and talented people in the world working for us. If you're creative, autonomous and love a challenge, we want to hear from you!