The role involves developing and deploying machine learning models. The individual will be responsible for building data pipelines and infrastructure. They will also contribute to the design and implementation of AI-powered features. The position requires working with large datasets to extract insights and improve model performance.

The role requires proficiency in Python and SQL for data manipulation and analysis. Experience with cloud platforms such as AWS is necessary. Familiarity with containerization technologies like Docker and orchestration tools such as Kubernetes is expected. The position also requires hands-on experience with machine learning frameworks including TensorFlow PyTorch and Scikit-learn. A strong understanding of MLOps principles and data engineering practices is essential for success in this role.