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Krishna Sahith Poruri
Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps
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About
ML/LLM engineer who built a production RAG system (GPT-4 + FAISS + FastAPI) to deliver fast, grounded answers from proprietary documents, optimizing for sub-200ms latency and high-concurrency scale. Strong MLOps/observability background: drift monitoring with Prometheus + Streamlit, automated retraining via Airflow, Kubernetes autoscaling, and MLflow-managed model lifecycle, plus inference cost reduction through quantization and structured pruning.
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Key Strengths
- Built and deployed production RAG system over proprietary documents (GPT-4 + FAISS + FastAPI)
- Reduced hallucinations via retrieval optimization and stable prompting
- Performance engineering for sub-200ms latency and high-concurrency serving
- Implemented drift monitoring with embedding/retrieval-score logging and automated retraining triggers
- Cost optimization using quantization (8-bit/4-bit) and structured pruning while maintaining accuracy
- End-to-end MLOps orchestration using Airflow, Kubernetes autoscaling, and MLflow model/version management
- Reliability engineering with modular agent design, guardrails, and comprehensive testing (unit/integration/simulations/benchmarks)
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