Embedded AI
Job Description
- Embedded Systems Experience: Proven experience in embedded systems software development and hardware integration.
- Deep Learning Frameworks: Hands-on experience developing, training, and optimizing models using deep learning frameworks such as PyTorch, TensorFlow, or Keras.
- Model Deployment & Conversion: Strong background in converting and optimizing AI/ML models for deployment using tools like ONNX, TensorRT, OpenVINO, or TVM.
- Edge / Embedded AI Deployment: Practical experience deploying and executing deep learning models on resource-constrained embedded platforms and edge accelerators.
- Model Compression & Optimization: Demonstrated experience in deep learning model compression techniques, specifically Quantization (PTQ/QAT) and Pruning.
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