Strong proficiency in Python and its ecosystem for machine learning, data analysis, and web development Extensive experience with RESTful API development and deployment for ML tasks Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes) Knowledge of cloud platforms (AWS, GCP, or Azure) for deploying and scaling ML services Proven track record in rapid ML model prototyping using tools like Streamlit or Gradio Experience with distributed task queues and scalable model serving architectures Understanding of monitoring, logging, and observability best practices for ML systems