The candidate should have to design, build, optimize, and support new and existing data models and processes based on the client's requirements.
Need to build, deploy, and manage data infrastructure that can adequately handle the needs of a rapidly growing data-driven organization.
Should be able to establish scalable, efficient, automated processes for large dataset analysis, model development, and validation.
Must be able to support, test, deploy, and maintain the AWS ecosystem from an infrastructure standpoint (Hybrid Cloud SDK upgrade, security fixes, etc.).
Need to coordinate data access and security to enable data scientists and analysts to easily access data whenever they need to and maintain the AWS ecosystem from an infrastructure standpoint.
Have to model, build, and test AI software to ensure it can take on large swaths of data and achieve desired results.
Need to work with a team of machine-learning and data engineers to ensure seamless AI development and integration.
Works with domain experts and AI Scientists to define annotation guidelines and drive the annotation efforts towards high-quality data.