# Data Scientist, New Grad - Model Optimization

**Company:** [Quadric](https://hotfix.jobs/companies/quadric)
**Location:** Burlingame, CA
**Role:** Data Science
**Salary:** $120k – $160k/yr
**Experience:** 0+ years
**Skills:** Python, PyTorch, TensorFlow, NumPy, Matplotlib, Plotly, Cnns, Transformers, Quantization, Pytorch Fx, Ptq, Qat, Tf-Lite, Onnx-Runtime, Tvm
**Posted:** 2026-05-20

> New grad Data Scientist role focused on model optimization and quantization for Quadric's custom GPNPU architecture. Own quantization workflows, extend quantization libraries, and build accuracy testing infrastructure. Requires strong Python/PyTorch skills and ML foundations.

## Job Description

## Responsibilities
- Develop and deploy quantization workflows for vision and language models, taking models from FP32 reference to deployable low-precision implementations that meet accuracy targets.
- Investigate per-layer numerical error, identify accuracy regressions, and propose calibration, PTQ, or QAT strategies to recover lost accuracy.
- Extend Quadric's quantization library with new operators, observers, and algorithms.
- Build and maintain numerical accuracy testing infrastructure and debug tooling for neural networks running on the GPNPU.
- Collaborate with graph compiler, kernel, and hardware teams to co-design solutions that exploit the GPNPU's numerical capabilities.

## Requirements
- B.S., M.S., or Ph.D. in CS, EE, Applied Math, or a related field, completed within the last year.
- Strong Python skills and fluency with PyTorch (or TensorFlow), NumPy, and data-viz tools (Matplotlib/Plotly).
- Solid machine learning foundations; working knowledge of CNNs and Transformers.
- Interest in quantization, numerical representation, fixed-point arithmetic, or low-level performance.
- Ability to read research papers, evaluate the core ideas, and reproduce key results.

## Nice-to-Haves
- Hands-on experience with quantization or model compression, or any of PyTorch FX/PTQ/QAT, TF-Lite, ONNX-Runtime, TVM, or MLIR Quant.
- Experience with embedded systems, DSPs, GPUs, or other accelerators.
- Published research, open-source contributions, or coursework projects in model optimization, efficient ML, or systems for ML.

## Compensation & Benefits
- Competitive salary and meaningful equity.
- Medical, dental, and vision plan options starting on day one.
- 401(k) retirement plan.
- Flexible paid time off (unlimited, non-accrual).
- Company-provided lunches and stocked kitchen when working in-office.
- Support for commuting, including monthly parking or Caltrain passes.

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