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Mallikarjuna Reddy Gayam
Mid-level AI/ML Engineer specializing in enterprise ML, MLOps, and Generative AI
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About
ML/LLM engineer who has shipped production RAG systems (LangChain + HF Transformers + FAISS) with hybrid retrieval and cross-encoder re-ranking, deployed via FastAPI/Docker/Kubernetes and monitored with MLflow. Also partnered with wealth advisors at Edward Jones to deliver a client retention model with SHAP-driven explanations and a dashboard that improved trust, adoption, and reduced high-value client churn.
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Key Strengths
- Built and deployed enterprise RAG knowledge assistant reducing employee time spent searching policy documents
- Deep retrieval optimization: chunking strategy tuning, hybrid BM25+dense retrieval, cross-encoder re-ranking with latency tradeoffs
- Production ML deployment and ops: FastAPI + Docker + Kubernetes with monitoring and reliability practices
- Experimentation and evaluation rigor: labeled datasets, precision/recall measurement, baseline comparisons
- Robust ML pipeline orchestration and governance using Airflow + MLflow, including drift detection and retraining triggers
- Strong stakeholder collaboration and explainability: translated advisor needs into features and delivered SHAP-based, business-friendly dashboard that drove adoption and reduced churn
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