Embedded AI Developer

As an Embedded Software Developer with a strong focus on AI/Machine Learning deployment, your role will involve the following key responsibilities: - Strong proficiency in C/C++ for embedded development. - Proficient in Python for AI development and scripting. - Hands-on experience with deep learning frameworks such as PyTorch. Experience with TensorFlow/Keras is a plus. - Strong understanding of embedded system architectures, microcontrollers, DSPs, and/or FPGAs. - Proven experience with deep learning model optimization techniques like quantization, pruning, and knowledge distillation. - Familiarity with different number formats (e.g., FP32, FP16, INT8) and their implications for embedded inference. - Experience with model conversion tools such as ONNX, OpenVINO, TensorRT, and TVM. - Excellent analytical and problem-solving skills, with a strong ability to debug and optimize complex systems. - Familiarity with hardware acceleration on edge devices, such as NPUs and GPUs. The company values your expertise in embedded software development with a focus on AI/Machine Learning deployment, as well as your strong programming skills in C/C++, Python, and deep learning frameworks like PyTorch. Your understanding of embedded system architectures, optimization techniques, number formats, and hardware acceleration will be crucial in your role. Your problem-solving skills and ability to debug and optimize complex systems will also be highly appreciated. As an Embedded Software Developer with a strong focus on AI/Machine Learning deployment, your role will involve the following key responsibilities: - Strong proficiency in C/C++ for embedded development. - Proficient in Python for AI development and scripting. - Hands-on experience with deep learning frameworks such as PyTorch. Experience with TensorFlow/Keras is a plus. - Strong understanding of embedded system architectures, microcontrollers, DSPs, and/or FPGAs. - Proven experience with deep learning model optimization techniques like quantization, pruning, and knowledge distillation. - Familiarity with different number formats (e.g., FP32, FP16, INT8) and their implications for embedded inference. - Experience with model conversion tools such as ONNX, OpenVINO, TensorRT, and TVM. - Excellent analytical and problem-solving skills, with a strong ability to debug and optimize complex systems. - Familiarity with hardware acceleration on edge devices, such as NPUs and GPUs. The company values your expertise in embedded software development with a focus on AI/Machine Learning deployment, as well as your strong programming skills in C/C++, Python, and deep learning frameworks like PyTorch. Your understanding of embedded system architectures, optimization techniques, number formats, and hardware acceleration will be crucial in your role. Your problem-solving skills and ability to debug and optimize complex systems will also be highly appreciated.