AI Kernel Engineer Intern

Quadric is redefining edge AI with the industry's first General Purpose Neural Processing Unit (GPNPU), enabling developers to run both neural network inference and conventional C++ code on a single programmable architecture. Our technology powers intelligent edge devices across automotive, industrial, robotics, and embedded systems.

Founded in 2016 and based in downtown Burlingame, California, Quadric is building the world's first supercomputer designed for the real-time needs of edge devices. Quadric aims to empower developers in every industry with superpowers to create tomorrow's technology, today. The company was co-founded by technologists from MIT and Carnegie Mellon, who were previously the technical co-founders of the Bitcoin computing company 21.

THE OPPORTUNITY

As a AI Kernel Engineer Intern , you will work closely with our senior AI Kernel Engineers to help enable a variety of AI/LLM models to run efficiently on the Quadric platform. This is a hands-on role where you will dive deep into hardware architecture and optimization techniques. You will gain invaluable experience developing, profiling, and optimizing kernel code, directly contributing to the performance of our AI inference stack.

Note: Our preference is for this internship to be based out of our Burlingame, California office. Candidates should be based in the Bay Area or able to relocate for the internship period and available to work on site.

WHAT YOU'LL DO

Develop & Implement

- Assist in developing AI/LLM kernels and operators on the Quadric platform for efficient inference.

Analyze & Profile

- Help profile kernel performance across compute, data, and parallelism to identify micro-architecture and software bottlenecks.

Code Optimization

- Work alongside senior engineers to optimize C/C++ code to maximize hardware utilization for different workloads.

Collaborate

- Partner across related areas of the AI inference stack to support team priorities and business goals.

Toolchain Contribution

- Contribute to improvements in the Quadric toolchain, compiler, and runtime.

WHAT SUCCESS LOOKS LIKE

Within your internship, you'll:

- Build a working understanding of kernel development and optimization for a GPNPU-class architecture.

- Contribute kernel or operator work that meaningfully improves AI inference performance.

- Develop hands-on fluency with performance profiling and hardware-aware code optimization.

WHAT WE'RE LOOKING FOR

Required

- Currently pursuing a Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, or a related field.

- Strong proficiency in C/C++ and Python.

- Solid foundational understanding of computer architecture and hardware-software interaction.

- Demonstrated capability in problem-solving, debugging, and clear technical communication.

Preferred

- Academic or project experience with model and kernel inference performance profiling.