Valeo
Linkedin · Posted yesterday
Embedded AI
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Indexed description
- Experience in embedded software development with a strong focus on AI/Machine Learning deployment.
- Programming Skills: Proficient in Python for AI development and scripting.
- Deep Learning Frameworks: Hands-on experience with deep learning frameworks such as PyTorch. Experience with TensorFlow/Keras is a plus.
- Embedded Systems: Strong understanding of embedded system architectures, microcontrollers, DSPs, and/or FPGAs.
- Optimization Techniques: Proven experience with deep learning model optimization techniques (quantization, pruning, knowledge distillation).
- Number Formats: Familiarity with different number formats (e.g., FP32, FP16, INT8) and their implications for embedded inference.
- Conversion Tools: Experience with model conversion tools (e.g., ONNX, OpenVINO, TensorRT, TVM).
- Problem-Solving: Excellent analytical and problem-solving skills, with a strong ability to debug and optimize complex systems.
- Experience with C/C++ for embedded development.
- Familiarity with hardware acceleration (e.g., NPUs, GPUs on edge devices).
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