Machine Learning Engineer (On-device Learning SW)
Qualcomm
- United States
- United States
À propos
Qualcomm Technologies, Inc. is seeking talented AI software engineers to enable AI technologies on edge devices. The role involves developing embedded AI software for training and fine-tuning neural network models on Qualcomm hardware, collaborating with cross-functional teams to implement high-quality solutions for new ML operators and enhancing the ML/AI software stack.
Responsibilities : • Development of end-to-end embedded AI software to train and finetune neural network models on Qualcomm leading edge hardware with optimal resources. • Design and enhance the implementation of ML/AI SW stack, kernels, and runtime software to improve performance and power efficiency. • Collaborating with our AI Processor Hardware team to implement high-quality solutions for new ML operators/layers that optimally utilize new capabilities in next-gen AI processors. • Development of debugging/profiling tools and user-friendly SDKs for customers to foster rapid deployment of their new use cases.
Qualifications : Required : • Bachelors degree in Computer Science, Engineering, Information Systems, or related field.
Preferred : • 1 year of work experience in a relevant field. • Excellent programming capabilities with C/C++ and Python. • Knowledge of deep learning and ML frameworks (i.e. PyTorch). • Strong software design, development, and debugging skills. • Knowledge of Android programming is plus. • Optimization of algebraic operations in algorithms for HW cores is a plus. • Knowledge in neural network model training is a big plus. • Knowledge in neural network model quantization is a big plus. • Experience with Qualcomm QNN SDK is a big plus.
Company :
Qualcomm designs wireless technologies and semiconductors that power connectivity, communication, and smart devices. Founded in 1985, the company is headquartered in San Diego, USA, with a team of 10001+ employees. The company is currently Late Stage.
Compétences linguistiques
- English
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