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improve model accuracy and efficiency.\nCollaborate with data scientists, software engineers, product managers, and other stakeholders.\nDeploy and monitor machine learning models in production.\nTroubleshoot model performance, data quality, and production issues.\nStay updated with the latest developments in machine learning, deep learning, and AI.\n\nRequirements: \n3-7 years of hands-on experience in machine learning / AI engineering.\nStrong programming skills in Python.\nStrong understanding of machine learning algorithms and concepts.\nExperience with Scikit-learn, Pandas, NumPy, and other relevant ML libraries.\nHands-on experience with deep learning frameworks such as PyTorch or TensorFlow.\nGood understanding of SQL and experience working with structured/unstructured data.\nExperience with model deployment and serving using tools/frameworks such as FastAPI, Flask, Docker, etc.\nUnderstanding of the ML lifecycle, model evaluation, experimentation, and monitoring.\nFamiliarity 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