quadric, Inc

Quadric provides a general-purpose neural processing unit (GPNPU) and software that enable high-performance on-device AI inference without splitting workloads across separate processors. It licenses…

AI Processor IPAutomotive SafetyLarge Language ModelsMachine LearningML InferenceNeural Processing UnitSoC DesignVision Transformersquadric.io

quadric, Inc

AI Processor IPAutomotive SafetyLarge Language ModelsMachine LearningML InferenceNeural Processing UnitSoC DesignVision Transformersquadric.io

HQBurlingame, US

Team Size64

Open Jobs11

Total Funding$74M

Latest Fundraise5 months ago

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AI Inference Engineer

On-SiteBurlingame, US

On-Site • Burlingame, US

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Quadric has created an innovative general purpose neural processing unit (GPNPU) architecture. Quadric's co-optimized software and hardware is targeted to run neural network (NN) inference workloads in a wide variety of edge and endpoint devices, ranging from battery operated smart-sensor systems to high-performance automotive or autonomous vehicle systems. Unlike other NPUs or neural network accelerators in the industry today that can only accelerate a portion of a machine learning graph, the Quadric GPNPU executes both NN graph code and conventional C++ DSP and control code.

Role:

The AI Inference Engineer in Quadric is the key bridge between the world of AI/LLM models and Quadric unique platforms. The AI Inference Engineer at Quadric will 1port AI models to Quadric platform; 2optimize the model deployment for efficient inference; 3profile and benchmark the model performance. This senior technical role demands deep knowledge of AI model algorithms, system architecture and AI toolchains/frameworks.

Responsibilities:

Quantize, prune and convert models for deployment
Port models to Quadric platform using Quadric toolchain
Optimize inference deployment for latency, speed
Benchmark and profile model performance and accuracy
Develop tools to scale and speed up the deployment
Make Improvement to SDK and runtime
Provide technical support and documents to customers and developer community

Requirements

Requirements:

Bachelor’s or Master’s in Computer Science and/or Electric Engineering.
5+ years of experience in AI/LLM model inference and deployment frameworks/tools
experience with model quantization (PTQ, QAT) and tools
experience with model accuracy measures
experience with model inference performance profiling
experience with at least one of the following frameworks: onnxruntime, Pytorch, vLLM, huggingface-transformer, neural-compressor, llamacpp
Proficiency in C/C++ and Python
Demonstrate good capability in problem solving, debug and communication

Benefits

Health Care Plan (Medical, Dental & Vision)
Retirement Plan (401k, IRA)
Life Insurance (Basic, Voluntary & AD&D)
Paid Time Off (Vacation, Sick & Public Holidays)
Family Leave (Maternity, Paternity)
Short Term & Long Term Disability
Training & Development
Work From Home
Free Food & Snacks
Stock Option Plan