Data Science Intern - Quantization & Model Optimization

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

Benefits offered by this job

Catered lunch

Downtown Burlingame office

Innovative disruption culture

Job summary

Quadric is seeking a data science intern to optimize models for our GPNPU architecture. You will work under a senior data scientist mentor on quantization and accuracy testing, contributing to the quantization library and debugging infrastructure.

Based in Burlingame, CA, this internship emphasizes hands-on tooling, calibration data, and real-world model optimization on vision and language models. Remote work is not indicated and relocation to the Bay Area is preferred.

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 under mentor guidance.
• Build calibration datasets and tooling to visualize per-layer error and distribution statistics for debugging.
• Contribute to numerical accuracy testing infrastructure and debugging tooling for the quantization library.

Skills

Python

PyTorch

TensorFlow

NumPy

Data visualization

Education

B.S./M.S./Ph.D. in CS/EE/Applied Math

Tools

Matplotlib

Plotly

Job description

Quadric is seeking a data science intern to optimize models for our GPNPU architecture. You will work under a senior data scientist mentor on quantization and accuracy testing, contributing to the quantization library and debugging infrastructure.

Based in Burlingame, CA, this internship emphasizes hands-on tooling, calibration data, and real-world model optimization on vision and language models. Remote work is not indicated and relocation to the Bay Area is preferred.