Data Science Intern - Model Optimization

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:

You will join the data science team for internship focused on model optimization for Quadric's custom GPNPU architecture. Working alongside a senior data scientist mentor, you will contribute to quantization library and/or numerical accuracy testing/debugging infrastructure.

Responsibilities:

* Run and contribute to new quantization workflows on vision and language models under mentor guidance.

* Build calibration datasets and tooling to visualize per-layer error and distribution statistics for debugging.

* Contribute to numerical accuracy testing infrastructure, numerical validation debug tooling of neural networks, and quantization library.