Hi there, it's Varshani Reddy Patlolla, and I'm thrilled to share a bit about myself with you! I'm a tech enthusiast through and through, with a constant desire to innovate and make a difference in the world of computer science. Whether I'm working on a machine learning project, developing a new app, or diving into big data, I'm always eager to learn and explore new frontiers in technology.
My background in computer science and engineering has provided me with a strong foundation in programming languages like Python, Hive, C++, SQL, Java and more, as well as frameworks and libraries like TensorFlow, OpenCV, and Scikit. These tools have been instrumental in my work as a Senior Software Engineer at Huawei Technologies India Pvt. Ltd., where I've had the opportunity to develop and deploy cutting-edge solutions for complex problems.
Outside of work, I enjoy exploring the great outdoors, reading up on the latest tech trends, and spending time with family and friends. I'm always looking for new ways to challenge myself, whether it's taking on a new project or tackling a difficult hike.
All in all, I'm proud of what I've accomplished so far, but I know there's still so much more to do. I'm excited to see where my passion for technology will take me next, and I can't wait to continue pushing the boundaries of what's possible in the world of computer science.
Projects
Skills
Experience
- Huawei - Senior Software EngineerAugust 2020 - July 2022
Developed and automated 30 Hive tasks to analyze logs and generate tags/features, streamlining workflows in the WiseOper portal. Designed and developed 11 risk detection models in Python, utilizing ML libraries for high accuracy. Orchestrated over 100 Hive tasks for feature calculation, contributing to improved risk assessment with over 92% accuracy. Took ownership of configuring end-to-end DevOps for ML models, reducing development time by more than 60%. Resolved resource allocation, docker images, and model deployment issues in AIdevops MTP environments. Developed 20+ components to manage requests for deployed ML models, handling version deployments and ensuring seamless service delivery. Oversaw service deployments in the AIdevops MEP Production environment, ensuring efficient resource and AZ allocation. Collaborated effectively with cross-functional teams to troubleshoot DevOps issues during Model Deployment. Thoroughly documented end-to-end processes and rulebooks for AIdevops, providing clear guidelines for ML model deployment and management.