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Shruti Pangare
Junior AI/ML Software Engineer specializing in LLMs and data-intensive systems
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AI/backend engineer who has owned production applied-ML systems end to end, including a Jitsi meeting intelligence platform with custom RoBERTa boundary detection, LLM summarization, and automated retraining from user feedback. Also has healthcare AI experience building a diabetes medication titration system with strict validation, drift monitoring, and safety guardrails—showing both product speed and high-stakes engineering rigor.
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Key Strengths
- end-to-end ownership of production AI backend systems
- strong latency-driven backend architecture tradeoff judgment
- built async processing pipelines that eliminated 504 timeouts
- improved topic boundary detection F1 from 84% to 91% in 6 weeks
- reduced transcript processing cost from $0.15 to $0.04
- rapid MVP scoping and execution in ambiguous early-stage environments
- designed feedback loops that turned user corrections into retraining data
- practical observability and incident response mindset
- defense-in-depth approach for high-stakes healthcare AI systems
- schema-based LLM safety controls that cut rejection rate from 8% to under 1%
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