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Dhyey Desai
Intern AI/ML Engineer specializing in RAG, multimodal AI, and LLM systems
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About
Built and shipped 'PetPulse,' a production AI pet-health note system that records voice notes, transcribes them, converts transcripts into structured symptom/event data, and supports grounded Q&A over a user’s notes and vet PDFs. Demonstrates full-stack LLM product execution (FastAPI + GPT-4 + Firebase), with concrete reliability/performance work (async endpoints, caching, RAG/embeddings, function calling) and user-centered iteration with a non-technical product stakeholder.
Experience
Education
Key Strengths
- Built and deployed an end-to-end LLM product (voice notes → structured events → Q&A) using FastAPI, GPT-4, and Firebase
- Performance optimization for LLM apps (caching to reduce repeated model calls; async endpoints to keep latency low)
- Reliable multi-device data synchronization using Firebase real-time updates
- Applied function calling to map natural-language questions to appropriate chart/visualization outputs
- Pragmatic orchestration with Docker Compose for multi-service deployments (API, worker, emulators) across dev/prod
- Metrics-driven evaluation of AI workflows (accuracy, latency, cost) using labeled test sets and iterative prompt/schema refinement
- Strong collaboration with non-technical stakeholders via clickable prototypes and tight feedback loops to simplify UX
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