Responsibilities :

- Design and develop web-based dashboards for monitoring ML inference services.

- Design and develop web-based tools to manage and visualize the Search CI/CD and release workflows.

- Onboard new ML models onto the existing platform with standardized training automation and interfaces.

- Maintain and enhance CI/CD pipelines for Search and ML services.

- Operate sign-off and deployment processes, ensuring daily release sign-off.

- Maintain and optimize training data preparation pipelines leveraging the latest big data tools, with an emphasis on cost-effectiveness and reliability.

Required Skillset :

- Demonstrated expertise in building and managing end-to-end MLOps pipelines using AWS SageMaker and related cloud-native tools.

- Proficiency in containerization technologies such as Docker and Kubernetes for deploying scalable ML services.

- Strong programming skills in Python, with a focus on writing clean, maintainable code for data processing and model orchestration.

- Ability to communicate complex technical concepts effectively to stakeholders and collaborate within a high-performing, agile team environment.

- Experience in managing cloud infrastructure and security best practices within an AWS environment.

- A Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.