AI Inference Optimization Engineer

About the role

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 member of our AI Application team, you'll own getting the latest AI models running fast and accurately on the GPNPU, from CNN perception models to LLMs and VLAs for automotive, robotics and AI-PC. You'll profile real workloads, write and tune kernels, choose quantization strategies, and build the tools that make model deployment repeatable.

WHAT YOU'LL DO

Analyze and optimize performance on GPNPU

- Deploy and profile models on GPNPU, from vision/perception to LLM/VLM/VLA

- Analyze the accuracy and choose the best quantization scheme

- Write and tune kernels and optimize model compute graphs on GPNPU, balance speed and accuracy

Create efficient flows to convert and deploy models on GPNPU

- Develop efficient tools and flows to speed up the model deployment, including profiling, tracing, visualization tools to find bottlenecks and agentic automation

- Customize open-source model optimization/quantization tools

- Integrate and automate model pruning, sparsification, quantization in the workflow

WHAT SUCCESS LOOKS LIKE

Within your first 6-12 months, you’ll:

- Deploy 5 new models on GPNPU independently, meeting accuracy targets

- Deliver a 2x speedup on a model through kernel, model compression or dispatch work

- Ship a deployment or an optimization tool the team uses every day

WHAT WE'RE LOOKING FOR

REQUIRED

- 3+ years experience in AI model deployment or kernel optimization

- BS/MS in CS/CE or related fields

- Strong C/C++ and Python

- Hands-on performance analysis: profilers, roofline/bandwidth reasoning, finding compute vs memory bottlenecks

- Hands-on experience with quantization (PTQ/QAT, int8/int4) and debugging accuracy loss

- Has written performance-critical kernels (CUDA, Triton, OpenCL, SIMD intrinsics or DSP)

Fluent with AI coding agents (e.g. Claude Code, Cursor), and interested in building agent-driven workflows for kernel and model bring-up

PREFERRED

- Hands-on experience in pruning and sparsification