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The position involves two main areas of focus: Software and Data Engineering, and MLOps Engineering. In the Software and Data Engineering aspect, you will utilize your expertise in Java and Kubernetes to build and maintain robust data solutions. This includes developing DevOps and monitoring solutions, as well as having a strong knowledge of the Software Development Life Cycle (SDLC). You will be responsible for building and managing dozens of data pipelines to source and transform data based on business requirements. In the MLOps Engineering role, you will implement and manage machine learning models in production environments, ensuring the reliability and scalability of ML workflows using tools like MLflow, Kubeflow, and AWS SageMaker. Additionally, you will be expected to quickly learn new technologies by applying your current skills, staying ahead of industry trends and advancements, and self-identifying the need for new skills to be developed and adopted into your skill set within a month's time.
