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Rakesh Deshalli Ravi
Mid-level Data Science & AI Engineer specializing in LLMs and cloud ML platforms
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Built and deployed an LLM-powered mental health therapy assistant at AppHealth that segments users by stress level and delivers personalized, non-medical guidance. Implemented healthcare-focused safety guardrails (secondary LLM output filtering) and a multi-agent router workflow validated via statistical tests and therapist review, then scaled training/inference on AWS (EC2/Lambda/DynamoDB) with Kubernetes.
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Key Strengths
- Built and deployed a production mental-health therapy assistant using an LLM
- End-to-end data acquisition strategy (online research + interviews + therapist-sourced data) to create representative training data
- Iterative model improvement loop (testing, identifying failure modes, collecting more data, re-fine-tuning)
- Implemented safety controls to prevent medical advice (output barrier + secondary LLM output checker)
- Designed and evaluated a multi-agent workflow with a router agent; tested routing consistency across 50–150 similar queries
- Validated subjective outputs with therapists to ensure alignment with professional guidelines
- Scaled training/inference using AWS and Kubernetes; handled high API request volume via EC2 scaling
- Balanced quality vs cost by managing token limits through prompt shortening and fine-tuning
- Effective communication of LLM concepts and progress to non-technical stakeholders (therapists, CEO)
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