Computer Vision, Embedded AI, and Machine Learning initiatives.
The ideal candidate should have strong hands-on experience in AI/ML model development, optimization, and deployment on edge devices, along with expertise in TensorFlow Lite, PyTorch Mobile, ONNX, Python, C/C++, computer vision, and embedded systems.
The role involves developing lightweight AI inference pipelines, optimizing models for resource-constrained environments, integrating AI solutions with embedded and IoT platforms, and enabling real-time AI-powered decision-making at the edge.
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