Roles and Responsibilities

• Design and develop the ML infrastructure, including data ingestion, storage, and management systems.
• Implement and maintain version control systems for ML models and datasets.
• Develop and deploy automated ML workflows using tools such as TensorFlow, PyTorch, or Scikit-learn.
• Collaborate with data scientists to develop and deploy ML models into production environments.
• Ensure the smooth operation of deployed models by monitoring performance and identifying potential issues.
• Develop and maintain documentation for ML infrastructure and workflows.

Required Qualifications

• Bachelor's degree in computer science, data science, mathematics, or a related field.
• Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
• Advanced proficiency with Python, Java, and R code writing.
• Experience working with machine learning frameworks like Theano, Tensorflow, Caffe, etc.

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