Nuvia
Qualcomm China
General Summary:
Job overview:
As a member of Qualcomm China's engineering team dedicated to automotive infotainment and ADAS platforms, you will play a pivotal role in advancing embedded deep learning solutions. We are seeking skilled engineers with expertise in machine learning to drive innovation and development in this dynamic domain.
Our objective is to seamlessly integrate high-performance software with advanced hardware, enabling rapid execution of deep neural networks. This approach is designed to optimize and enrich the driving experience—particularly in ADAS and GenAI applications—by leveraging the full potential of Snapdragon chipsets embedded within modern vehicles.
In this position, you will work extensively with neural network frameworks such as PyTorch and ONNX, contributing to the continuous enhancement of our neural network inference engine to support cutting-edge deep learning models emerging from both academia and industry. You will also be responsible for optimizing and fine-tuning these applications for Qualcomm’s next-generation hardware acceleration platforms, including DSP, GPU, and CPU, ensuring maximum performance and efficiency.
The work scope includes but not limit to:
Development and bug fix in Qualcomm Neural network SDK (QNN/AI Engine Direct SDK). Neural network operator development, with Hexagon DSP or SIMD accelerator. Performance and accuracy tuning and optimizations with QC AI Engine Direct SDK. Algorithms prototype design and implementation for user defined operators. Practices on quantization aware training and post-training quantization. Co-work with our global team on new feature design and implementation. Support testing team to improve the quality of our products. Support customer to deploy their neural networks with highest performance and accuracy.
Minimum Qualifications:
• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.Minimum Qualifications:
2-3 years C/C++ programming experience on Linux or other embedded system. Excellent communication skills (verbal, presentation, written). Ability to collaborate across a globally diverse team, have a good sense of responsibility and teamwork. Experienced with Python programming. Have the concept of SDK development for variant system platforms. Familiar with ARM architecture.
Preferred Qualifications:
Familiar with popular quantization framework is a plus: ONNX QDQ, Pytorch, TensorFlow, PPQ, TensorRT. Enthusiasm in machine learning technology. Hand-on experience in design/implementation of deep learning networks via modern frameworks. Excellent software design, problem solving, debugging, documentation and presentation skills and proved experiences. Development on deep learning inference framework relevant practical experience is a plus, such as QNN, TfLite, NCNN, TNN, MACE, etc. Familiar with fixed-point quantitative algorithms and implementation. Familiar with popular deep learning frameworks: TensorFlow, Pytorch, ONNX, etc. Familiar with parallel programing, such as OpenCL, NEON, OpenMP, Cuda, etc. DSP software development and algorithm implementation, familiar with Hexagon/HVX is a big plus. Having quantization experience on TensorFlow or Pytorch is a plus. Experienced with LLM/LVM or ASR/NLP related models is a plus.
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