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Sri Mounika Jammalamadaka
Mid-level AI/ML Engineer specializing in GenAI, LLMs, and data platforms
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About
Built and helped deploy a production RAG-based LLM assistant for HVAC anomaly diagnostics, partnering closely with field engineers and operations teams to make AI outputs trustworthy in real workflows. Stands out for practical post-launch optimization work—improving retrieval quality, reducing hallucinations, and stabilizing non-deterministic behavior—which contributed to roughly a 40% reduction in diagnosis time.
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Key Strengths
- End-to-end ownership of LLM deployment from discovery through post-launch stabilization
- Applied RAG for HVAC anomaly diagnostics
- Reduced diagnosis time by about 40%
- Strong stakeholder alignment across field engineers, ops, data, and engineering
- Built trust-focused AI workflows grounded in real operational data
- Debugged non-deterministic AI behavior in production by isolating retrieval inconsistencies
- Improved production stability with metadata filters, recency weighting, and fallback logic
- Designed reliable data pipelines for messy real-world inputs using validation and normalization layers
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