Quadric has created an innovative general purpose neural processing unit (GPNPU) architecture. Quadric's co-optimized software and hardware is targeted to run neural network (NN) inference workloads in a wide variety of edge and endpoint devices, ranging from battery operated smart-sensor systems to high-performance automotive or autonomous vehicle systems. Unlike other NPUs or neural network accelerators in the industry today that can only accelerate a portion of a machine learning graph, the Quadric GPNPU executes both NN graph code and conventional C++ DSP and control code.
Role:
The AI Kernel Engineer in Quadric plays the key role to enable a large number of AI kernels/operators to run efficiently on the Quadric platform. The AI Kernel Engineer at Quadric will [1] develop a highly efficient Quadric kernel library for a variety of AI/LLM models; [2] analyze the performance and optimize the kernel for different hardware configurations; This senior technical role demands deep knowledge of hardware architecture, compiler toolchain and optimization techniques.
Responsibilities:
Requirements
Benefits
Quadric licenses an AI processor architecture optimized for on-device inference. Only the Quadric Chimera GPNPU (general purpose neural processing unit) delivers high AI/ML inference performance while also running C++ code without forcing the developer to artificially partition application code between two or three different processors. Quadric's Chimera GPNPU processor IP core scales from 1 to 864 TOPS and seamlessly intermixes scalar, vector and matrix code.
