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Pavithran Gnanasekaran
Junior AI/ML Engineer specializing in RAG, LLM apps, and cloud-native data platforms
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About
Internship-built full-stack systems spanning HR employee-record portals and internal data-quality dashboards (Flask + SQL + React), emphasizing data integrity and rapid MVP iteration. Also implemented Flask microservices with RabbitMQ for distributed task processing, addressing duplication/ordering issues with idempotency, durable queues, and correlation-ID logging; delivered quantified productivity gains for HR teams.
Experience
Education
Key Strengths
- Shipped MVPs quickly and iterated via frequent incremental releases based on direct user feedback
- Strong data integrity focus (backend validation + DB constraints like PK/UK/FK/NOT NULL, correct monetary types)
- Designed maintainable React/TypeScript front ends with feature-based organization and strong typing to reduce regressions
- Improved performance by pushing complex filtering/sorting into optimized database queries behind stable REST APIs
- Microservices reliability at scale (handled message ordering/duplication with idempotency, durable queues, acknowledgments)
- Implemented centralized logging with correlation IDs to speed cross-service debugging
- Built internal HR data validation/reporting dashboard with measurable impact (50%+ more issues found; 70% less correction time)
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