Dedeepya Yarra

Machine Learning Mlops Engineer @eBay

US

Implementing Agile development methodology within the cross-functional team and acting as a liaison between the business user group and the technical team.• Developed, implemented, and managed scalable operations research and machine learning pipelines for data preprocessing, model training, validation, and deployment on Databricks and Gurobi Cloud using Terraform.• Collaborated closely with data scientists and software engineers to deploy machine learning models into production, optimizing their performance for real-world scenarios.• Established robust monitoring and alerting systems to ensure the health, availability, and accuracy of deployed models, utilizing tools such as Datadog and custom monitoring scripts. • Worked in tandem with the DevOps team to automate and streamline the deployment and management of machine learning systems, enhancing efficiency and reliability.• Continuously improved ML Ops processes by identifying bottlenecks, implementing best practices, and staying up-to-date with the latest advancements in the field.• Conducted data preprocessing, feature engineering, and model evaluation to optimize model performance.• Utilized cloud platforms (e.g, AWS, Azure) for scalable model training and deployment, improving system efficiency and cost-effectiveness.• Integrated CI/CD pipelines for automating model updates and monitoring model drift.• Led efforts to improve model interpretability and explainability, enabling better decision-making and compliance with regulatory requirements.• Collaborated with data engineers to create data pipelines, ensuring data quality and reliability for machine learning tasks.Conducted regular knowledge-sharing sessions to educate team members on MLOps best practices, fostering a culture of continuous learning and innovation.

Jawaharlal Nehru technological University - Narsaraopet

Bachelor of Technology - BTech

University of North Texas

Master's degree