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Parnashri Nandam
Mid-level AI Engineer specializing in LLMs, RAG, and production ML systems
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About
Backend engineer who built an AI-powered grant matchmaking platform for researchers and professors, combining semantic matching, embeddings, and Semantic Scholar enrichment with rule-based eligibility filters. Stands out for pragmatic AI engineering: they focused on reliability through confidence scoring, logging, manual validation, and production-minded backend design.
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Key Strengths
- Designed backend systems for AI-driven grant recommendation
- End-to-end ownership of recommendation workflow from scoping to launch
- Combines AI matching with rule-based filters for reliability
- Strong backend architecture skills with FastAPI/Flask and PostgreSQL
- Built automated data ingestion and cleanup workflows with background jobs
- Practical evaluation mindset using manual verification, sample profiles, and engagement metrics
- Balances speed vs accuracy with query optimization and caching
- Able to create structure in ambiguous product environments
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Experience
Education
Awards
Skills
Languages
Publications
2 publications
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