Software Engineer Machine Learning

Revanth Gummadavelly

Orlando, FL +1-689-***-**** ad5d6a@r.postjobfree.com www.linkedin.com/in/revanth-gummadavelly/ EDUCATION

University of Central Florida Orlando, FL

Master of Computer Science – GPA 4/4 August 2022 – April 2024 Coursework: Design and Analysis of Algorithms, Machine Learning, Advanced Database Systems, Parallel and Distributed Systems WORK EXPERIENCE

Software Engineer August 2023 – present

University of Central Florida Orlando, FL

• Led the end-to-end development of a Python application to collect and process daily health metrics from 200+ Fitbit-equipped participants, generating a dataset of over 1 million data points for research insights.

• Developed robust integration with Fitbit Web APIs and Selenium leveraging OAuth2.0 authentication to retrieve user data from Fitbit trackers and utilized AWS Lambda for data aggregation.

• Designed and implemented Python Flask-based RESTful services to facilitate participant and authentication management services, slashing participant onboarding time by 75%. Software Engineer July 2020 – August 2022

Entain Group India

• Collaborated with a 5-member Scrum team to design and develop a market management platform, enabling Entain sports traders to streamline operations across 25 betting markets for 7 major US sports, including NFL, NBA and other top leagues.

• Architected a high-performance Reactive Java Microservice using Spring WebFlux, for real-time betting market data streaming, enabling market updates for over 5k concurrent traders with a 60ms latency via Server-Sent Events.

• Built scalable Spring Boot RESTful APIs for fixture/market management operations and integrated them with Kafka in an event- driven architecture for asynchronous processing, reducing the market response time from 12 sec to 5 sec.

• Implemented Redis cache (NoSQL) for concurrency control and mitigated data conflict errors by 90% during concurrent odds and pricing updates by traders, ensuring system accuracy and a seamless betting experience.

• Designed responsive UI components in AngularJS to display live scores by leveraging Event Sourcing and RxJS to consume real-time score feeds and provided user-friendly controls to streamline trader workflows. Software Engineer April 2019 – July 2020

Accenture India

• Contributed to the development of a centralized marketing system for 6 Belgian Distributed Grid Operators, focusing on writing business logic for both the Business layer and Data layer utilizing Asp.Net (C#) and Object-Oriented Programming.

• Led performance optimization efforts for a critical Billing module through targeted MySQL DB indexing and SQL query and stored procedure fine-tuning, significantly reducing database response latency from 33ms to 2ms.

• Implemented CI/CD through Gitlab, following DevOps best practices to ensure reliable integration, testing, and deployment for the platform and applied Agile Software methodology to streamline SDLC, utilizing JIRA for sprint tracking.

• Conducted comprehensive log analysis to identify root causes and troubleshoot bugs in the production environment, resulting in efficient bug resolution and improved system stability.

• Automated server monitoring and health check tasks through scheduled Cron jobs using Node.js, reducing the operations team overhead by saving 15 manual hours per month. SKILLS

Languages: Python, Java, JavaScript, HTML, CSS3, SQL Programming: Data structures and Algorithms, Object Oriented Design, Design Patterns Frameworks: AngularJS, Spring Boot, React.js, Junit Databases: Cassandra, MySQL, Redis

Tools: Jira, Maven, Docker, Postman, Swagger, Git, GitLab CI/CD Others: AWS, REST API, Kafka, OAuth, XML, DevOps, Agile methodologies, Software Development Life Cycle PROJECTS

Dashboard for all the MORD schemes, India

• Led a team of 4 to design a dashboard UI with charting capabilities using React.js, D3.js as frontend and Node.js as backend, enabling 200+ Indian Government officials to track key metrics about all the schemes of the Ministry of Rural Development in real-time.

Cache Simulator Github link

• Developed a scalable Java cache simulator using Object Oriented Programming, supporting L1, L2, L3 caches with LRU, LFU, Optimal replacement policies, improving performance by 30% through LSTM model by forecasting future page requests. Clustering data to detect Network Intrusion Attacks using Genetic Algorithm Github link

• Implemented a research paper's findings to build a machine learning model utilizing Genetic Algorithm to classify network attacks into optimal cluster configurations, enhancing accuracy over traditional K-means clustering without exhaustive scenario evaluation.

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