Data Science Intern- Model Optimization

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.

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

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.

Quantization Workflows

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

Debugging Tooling & Analysis

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

Testing Infrastructure

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

Within your internship, you'll:

• Build a working understanding of quantization and numerical accuracy tradeoffs for a GPNPU-class architecture.

• Contribute tooling, calibration data, or infrastructure that meaningfully supports the quantization library or accuracy debugging.

• Develop hands-on fluency with model optimization and numerical validation workflows on real vision and language models.

Required

• Currently pursuing or recently graduated with a B.S., M.S., or Ph.D. in CS, EE, Applied Math, or a related field.

• Solid Python skills and comfort with PyTorch (or TensorFlow), NumPy, and basic data-viz tools (Matplotlib/Plotly).

• Coursework or project experience in machine learning; familiarity with CNNs and/or Transformers.

• Curiosity about quantization, numerical representation, fixed-point arithmetic, or low-level performance.

• Ability to read a research paper and discuss the core ideas.

Preferred

• Prior exposure to quantization, model compression, or any of PyTorch FX/PTQ/QAT, TF-Lite, ONNX-Runtime, TVM, or MLIR Quant.

• Any hands-on experience with embedded systems, DSPs, GPUs, or other accelerators.

Quadric is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, marital status, medical condition, or any other characteristic protected by applicable federal, state, or local law

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• E-Verify Participation Notice (English | Spanish)

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