Data Scientist - Model Optimization at Quadric

Burlingame, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Semiconductors, AutomotiveIndustries

Requirements

M.S./Ph.D. in CS, EE, Applied Math, or similar, with 5+ years in ML model optimization or data-science-driven research
Deep grasp of fixed-point arithmetic, quantization theory, and statistical calibration
Fluent in Python, PyTorch or TensorFlow, NumPy/Pandas/SciPy, and data-viz tools (Matplotlib/Plotly)
Hands-on with at least one quantization toolkit (PyTorch FX/PTQ/QAT, TF-Lite, ONNX-Runtime, TVM, MLIR Quant)
Working knowledge of CNNs, Transformers and DNN architectures

Responsibilities

Design statistically rigorous experiments to compare PTQ, QAT, pruning, and mixed-precision schemes on vision, language, and multimodal models
Build calibration datasets; develop Python notebooks/dashboards to track accuracy, latency, power, and memory trade-offs
Perform layer- and token-level error analysis to guide numerical-format choices
Partner with compiler team to convert your findings into turnkey SDK flows and reference configs
Publish internal whitepapers, external benchmarks, and present results to customers and at industry events
Monitor academic literature in compression and efficient inference; translate promising ideas into reproducible prototypes

Skills

Python

PTQ

QAT

Pruning

Mixed-Precision

Quantization

Fixed-Point Arithmetic

Statistical Calibration

Neural Networks

Model Optimization

Calibration Datasets

Error Analysis

Latency Optimization

Power Optimization

Quadric

Simplifies SoC design for machine learning

About Quadric

Quadric focuses on simplifying the design and programming of System on Chips (SoCs) specifically for machine learning applications. Their main product is the Chimera, a General-Purpose Neural Processing Unit (GPNPU) that combines matrix and vector operations with scalar control code in a single execution pipeline. This design allows developers to avoid splitting application code across different processors, making the development process more efficient. Quadric serves clients in the semiconductor industry, including SoC developers and manufacturers, who need to improve their machine learning capabilities. Unlike competitors, Quadric offers a comprehensive solution that includes both hardware and software tools, such as the Chimera LLVM C Compiler and the Chimera Instruction Set Simulator, enabling developers to design, simulate, and deploy their applications effectively. The goal of Quadric is to enhance the performance and ease of development for machine learning applications on SoCs.

Burlingame, CaliforniaHeadquarters

2017Year Founded

$42.1MTotal Funding

DEBTCompany Stage

Hardware, Enterprise Software, AI & Machine LearningIndustries

51-200Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

401(k) Retirement Plan

Company Equity

Risks

Increased competition from established semiconductor companies threatens market share.

Rapid AI advancements may outpace Quadric's current product offerings.

Potential IP disputes could lead to costly legal battles.

Differentiation

Chimera GPNPU integrates matrix, vector, and scalar operations in one pipeline.

Quadric's GPNPU runs C code, enhancing versatility for neural network operations.

Quadric offers a unified architecture for ML inference and C++ processing.

Upsides

Quadric's Series B funding boosts expansion of engineering and commercial teams.

Partnership with Ams Osram enhances smart sensing solutions for edge applications.

Quadric Developer Studio simplifies AI and ML application development.

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