Proficiency in deep learning frameworks such as TensorFlow and PyTorch is critical. TensorFlow offers scalability and production-ready deployment tools, whereas PyTorch is favored for its dynamic computation graph and ease of debugging. Mastery over one or both of these frameworks is fundamental for any machine learning engineer focusing on neural networks.
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