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Varaprasad Bathula
Intern AI/ML Engineer specializing in LLM applications and data infrastructure
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About
Hands-on LLM practitioner who built a production document-processing pipeline in Python, tackling long-document handling and latency with chunking/batching and a user-driven correction feedback loop. Experienced operationalizing AI workflows with Kubernetes (CronJobs, autoscaling, scheduled data cleaning and weekly retraining) and applying structured testing/evaluation (E2E, LLM-as-judge, HITL) while communicating solutions clearly to non-technical clients using visual diagrams.
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Key Strengths
- Built and deployed an LLM document-processing pipeline in Python
- Handled long-document constraints via chunking and batch processing
- Reduced latency through pipeline optimization and smaller-batch processing
- Implemented a user correction feedback loop with weekly review to improve model performance
- Production orchestration with Kubernetes (CronJobs, autoscaling, scheduled jobs, weekly retraining automation)
- Structured AI workflow testing approach (module/component, integration, end-to-end)
- Evaluation strategy using automated tests, LLM-as-judge, and HITL
- Model/retrieval/prompt selection using accuracy-latency-cost tradeoff framework
- Able to explain AI solutions to non-technical stakeholders using visual diagrams and sample outputs
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