The role involves developing and deploying machine learning models. It also includes building and maintaining data pipelines for model training and inference. The position requires working with large datasets to extract insights and improve model performance. The individual will contribute to the end-to-end lifecycle of machine learning solutions.

The role requires proficiency in Python and SQL for data manipulation and model development. Experience with cloud platforms such as AWS is necessary. Familiarity with containerization technologies like Docker and orchestration tools such as Kubernetes is also required. The position necessitates expertise in machine learning frameworks including PyTorch TensorFlow and Scikit-learn. A strong understanding of data manipulation libraries like Pandas and NumPy is essential.