Convert data science prototypes into production-ready, scalable models and services. Develop and maintain automated CI/CD pipelines for model training, testing, deployment, and rollback. Implement monitoring, logging, and alerting systems to track model performance, drift, and data anomalies in production. Manage model versioning, reproducibility, and containerization (e.g., Docker, Kubernetes). Requirements: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field. Proven experience in designing and implementing AI/ML models. Proven experience in designing and implementing AI/ML models and GenAI/Agentic solutions in production. Solid knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch). Experience with CI/CD pipelines and tools. Experience with containerization technologies (e.g., Docker, Kubernetes).