Distinguished Engineer – High Performance AI

About Nvidia

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.

Job Summary

We are looking for an outstanding Distinguished Engineer – High Performance AI to build groundbreaking agentic AI systems for the CUDA ecosystem. We build full-stack agentic AI platforms—spanning multi-agent runtimes and orchestration, data and evaluation pipelines, training and inference stacks, and GPU-accelerated execution—deeply integrated with NVIDIA’s software and hardware stack to advance accelerated computing end-to-end.

Key Responsibilities

• Set strategy and lead execution for agentic AI systems for the CUDA ecosystem, defining roadmaps and measurable success metrics (performance, quality, reliability, developer productivity).
• Co-design agentic system solutions with software, hardware and algorithm teams; influence and adopt new capabilities as they become available.
• Develop reproducible, high-fidelity evaluation frameworks covering performance, quality and developer productivity.
• Collaborate across the AI stack and help drive architecture and key technical decisions—from hardware through compilers/toolchains, kernels/libraries, frameworks, distributed training, and inference/serving—and with model and research/engineering teams.
• Scale impact through leadership: mentor and grow senior technical talent.

Requirements

• Bachelor’s degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); MS or PhD preferred.
• 17+ years industry and/or academia experience with AI systems development; strong exposure to building foundational models, agents or orchestration frameworks; hands-on experience with deep learning frameworks and modern inference stacks.
• Strong C/C++ and Python programming skills; solid software engineering fundamentals; ability to set engineering direction.