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HEMANTH KUMAR KOTTAPALLI
Mid-level Machine Learning Engineer specializing in GPU-accelerated LLMs and MLOps
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Built and deployed a production LLM-powered decision-support system for supply-chain planners that explains demand forecast changes using grounded retrieval from sales, promotion, inventory, and supplier data. Implemented strict anti-hallucination guardrails and latency optimizations, deployed as a real-time AWS API with monitoring, and reported ~15% forecast accuracy improvement and ~12% supply-chain risk reduction. Experienced orchestrating data/ML/LLM workflows with Airflow, LangChain/LangGraph-style patterns, and AWS Step Functions while partnering closely with non-technical business users via demos and example-based requirements.
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Key Strengths
- Built and deployed production LLM decision-support system for demand forecasting/planning
- Designed RAG-style system that grounds responses in sales/promotion/inventory/supplier data
- Strong hallucination prevention via strict retrieval/abstention rules
- Performance optimization (caching; using LLM for explanations not calculations)
- Production-grade deployment on AWS with monitoring and quality checks
- Delivered measurable business impact: ~15% forecast accuracy improvement and ~12% supply-chain risk reduction
- Effective collaboration with non-technical stakeholders through example-driven requirements and frequent demos
- Orchestration expertise across Airflow, LangChain/LangGraph-style flows, and AWS Step Functions
- Structured approach to agent/workflow testing and evaluation using real user cases, edge cases, and measurable metrics
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