Data Science Intern- Model Optimization

quadric technologies; Burlingame (CA); On-site; USD 69,000 - 79,000; Full time

Benefits offered by this job

Catered lunch

Downtown Burlingame

Innovative disruption

Job summary

Quadric in Burlingame, CA, is seeking an intern for the data science team to work on model optimization for its GPNPU architecture. You will contribute to the quantization library and to numerical accuracy testing under a senior mentor, with on-site work preferred.

As part of the internship you will build calibration data, tooling to visualize per-layer statistics, and help validate neural networks for vision and language models.

Qualifications

• 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.

Responsibilities

• Run and contribute to quantization workflows on vision and language models.
• Build calibration datasets and tooling to visualize per-layer error and distribution statistics for debugging.
• Contribute to numerical accuracy testing infrastructure and the quantization library.

Skills

Python

PyTorch

NumPy

Data Viz

Education

CS/EE/Applied Math degree

Tools

PyTorch

TensorFlow

Matplotlib/Plotly

Job description

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

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.

What You'll Do

Quantization Workflows

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

Debugging Tooling & Analysis

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

Testing Infrastructure

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

What Success Looks Like

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.

What We're Looking For

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.

What We Offer

The hourly salary range for this temporary position is $50-57/hr . This range reflects the full span of levels and geographies at which Quadric hires for this role. The actual hourly salary offered will depend on a number of factors, including the specific level of the role, years and depth of relevant experience, technical skills and competencies.

Quadric interns receive hands‑on experience working alongside industry experts in AI and semiconductor technology, with access to mentorship and meaningful project ownership from day one along with following

• Catered lunch each day in our office

• Downtown Burlingame office location, close to shops, cafes, and local amenities

• A work culture focused on innovative disruption

Equal Employment Opportunity

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

E-Verify and Right to Work Notices

Quadric participates in the E‑Verify program to confirm employment eligibility for U.S.-based roles. As part of this process, applicants may review the following notices, which explain your rights and our participation in E‑Verify. These notices are provided in English and Spanish.

• E‑Verify Participation Notice (English | Spanish)

• Right to Work Notice (English | Spanish)

No action is required from candidates during the application process. These notices are provided for informational purposes only.

Privacy

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