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Meghashree N
Mid-level AI/ML Engineer specializing in recommender systems, NLP, and cloud ML
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AI/ML engineer who has shipped both a safety-critical mental health RAG chatbot (Mistral 7B + Pinecone) with automated faithfulness/toxicity monitoring and a deep Q-learning investment recommendation engine at Lincoln Financial Group. Strong in production MLOps and orchestration (AWS Lambda/CloudWatch/SageMaker, Docker, AKS) and in translating regulated-domain requirements (clinical reliability, fiduciary duty) into measurable model constraints and monitoring.
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Key Strengths
- Built and deployed a production mental-health RAG chatbot with strict grounding to proprietary, expert-vetted resources
- Designed robust LLM safety/reliability controls (system-prompt constraints, faithfulness scoring, toxicity filtering)
- Implemented production monitoring with automated alerting (CloudWatch, rolling averages, latency SLAs)
- MLOps-style degradation detection (embedding drift analysis, context recall tracking) to trigger audits/updates
- Serverless orchestration for ML workflows (Lambda + CloudWatch rules triggering SageMaker retraining/serving)
- Designed deep reinforcement learning investment recommendation engine (DQL) with multi-objective reward balancing return and risk tolerance
- Translated non-technical/regulatory stakeholder requirements into measurable model constraints and explainability outputs
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