Vageesha Datta Ganapaneni
@vageeshadattaganapan
Software engineer specializing in full-stack development, scalable systems, and ML-enabled services.
What I'm looking for
I am a software engineer focused on building scalable full-stack systems and ML-enabled applications. I combine backend engineering, cloud deployment, and frontend development to deliver reliable, production-ready features.
During internships and full-time work, I improved transaction throughput, reduced API latency, and increased fraud-detection accuracy by integrating ML models and optimizing data pipelines. I design ETL and storage systems that handle millions of records with high reliability.
I have implemented CI/CD, containerization, and monitoring solutions using Docker, Kubernetes, AWS, and observability tools to enhance deployment stability and reduce fault detection time. I also create reusable libraries and APIs to standardize development and accelerate delivery.
My project work includes personalized recommendation platforms, FAISS-based semantic search and summarization tools, and secure healthcare portals with conversational support—each demonstrating production-minded engineering and measurable improvements in relevance, speed, and reliability.
Experience
Work history, roles, and key accomplishments
Software Engineer Intern
Rootstack
Jan 2025 - May 2025 (4 months)
Built and deployed full-stack modules with React.js and Flask, improving transaction throughput by 30% and reducing API latency via indexing, caching, and pooling strategies. Implemented scalable data pipelines and monitoring dashboards that cut fault detection time by 40%.
Software Engineer Intern
Fiserv
May 2023 - Aug 2023 (3 months)
Engineered Python backend services and ETL pipelines for transaction processing and real-time fraud detection, improving model accuracy by 17% and ensuring 99.9% reliability for millions of daily records. Automated deployments for zero-downtime rollouts.
Developed backend components and reusable Python libraries for enterprise workflow automation, reducing manual operations by 45% and cutting code redundancy by 35%. Optimized data modules processing 10M+ records, improving speed by 28% and deployed containerized CI/CD pipelines.
Education
Degrees, certifications, and relevant coursework
The University of Texas at Dallas
Master of Science, Computer Science
2022 - 2025
Master of Science in Computer Science with coursework in operating systems, machine learning, AI, computer vision, NLP, statistics for AI/ML, and web programming.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
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