Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Analyze existing data sets to identify patterns, trends, and insights that can enhance machine learning model development. Design, implement, and iterate on machine learning models to address specific business challenges and enhance product functionality. Build knowledge by keeping up with latest advancements in machine learning and artificial intelligence (AI), integrating new techniques and technologies into our MLOPS development process. Build and maintain Data/Solution Pipeline Engineering to ensure a robust and scalable data infrastructure that supports the training and deployment of machine learning models. Collaborate on data preprocessing and feature engineering to enhance the quality of input data for machine learning models. Design and optimize data structures in data management systems (Cloud platforms - Snowflake, GCP, Azure) to enable AI/ML solutions. Build custom software components and analytics applications. Create/Maintain CI/CD pipelines of machine learning solutions in the cloud environment. Implement strategies for deploying machine learning models into production environments. Responsible for selecting best model to meet both model performance and minimize compute costs. Establish and maintain monitoring systems to track the performance of deployed models and facilitate continuous improvement. Collaborate with the Product and Engineering teams to identify opportunities for integrating machine learning and Generative artificial intelligence capabilities into Project solutions/platform. Collaborate with the Product team to design a Tactical roadmap for the adoption of machine learning technologies, paradigms & frameworks following organizations best practices. Work in a technical team through development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics using machine learning and artificial intelligence. Communicate findings, insights, and recommendations to both technical and nontechnical stakeholders in a clear and accessible manner.