Hybrid
Full Time
Experience: 5+ years of 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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