Data science with AI Professional

Required Qualifications:
Bachelor s or Master s degree in Computer Science, Engineering, Data Science, or a related field. 5+ years of hands-on experience as an AI Engineer, Machine Learning Engineer, or a similar role focused on building and deploying AI/ML solutions. Strong proficiency in Python and its relevant ML/data science libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Extensive experience with at least one major deep learning framework such as TensorFlow, PyTorch, or Keras. Solid understanding of machine learning principles, algorithms (e.g., regression, classification, clustering, ensemble methods), and statistical modeling. Experience with cloud platforms (e.g., AWS, Azure, GCP) and their AI/ML services (e.g., SageMaker, Azure ML, Vertex AI). Proven experience with MLOps concepts and tools for model lifecycle management (e.g., MLflow, Kubeflow, Sagemaker MLOps, Azure ML Pipelines). Strong SQL skills for data manipulation, analysis, and feature extraction from relational databases. Experience with data preprocessing, feature engineering, and handling large datasets. Familiarity with software development best practices including version control (Git), code reviews, and CI/CD. Excellent problem-solving skills and the ability to work on complex, ambiguous problems. Strong communication and collaboration skills to work effectively with cross-functional teams.