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Vamsidhar Vuddagiri
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
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About
Built an LLM-powered academic research assistant for a professor (LangChain + OpenAI + arXiv) focused on synthesizing papers quickly, with emphasis on reliability (ReAct prompting, citation verification) and cost control (caching). Has production MLOps/orchestration experience at Cisco and HCL Tech using Kubernetes, plus MLflow and GitHub Actions for lifecycle management and CI/CD.
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Key Strengths
- Built and deployed an LLM-based academic research assistant (Agent AI) using LangChain + OpenAI + arXiv
- Reliability engineering for LLM apps: structured ReAct prompts, error handling, retries/fallback paths
- Hallucination mitigation via citation verification / fact-check mechanisms
- Cost optimization for LLM systems through intelligent caching and call minimization
- Production orchestration experience with Kubernetes for scalable, lower-latency AI inference
- Operationalized model monitoring and retraining workflows on Kubernetes to reduce model drift
- Strong testing discipline for agents (unit, integration, adversarial) with quantitative and qualitative evaluation
- Experience collaborating with non-technical stakeholders to iterate on usability and requirements
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