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Saloni Patadia
Mid-level Machine Learning Engineer specializing in LLM systems and healthcare data automation
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About
React performance-focused engineer who contributed performance patches back to an open-source context+reducer state helper after profiling and fixing excessive re-renders in an enterprise project management platform at Easley Dunn Productions. Also built an end-to-end LLM-driven pipeline at Prime Healthcare to normalize millions of supply-chain records, reducing defects by 80% and saving 160+ hours/month.
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Key Strengths
- Diagnoses React performance bottlenecks using profiling (flame graphs/profiler) and controlled benchmarks
- Improves state management performance via selector-based subscriptions and referential stability to reduce unnecessary re-renders
- Open-source collaboration: RFC-style issue, design tradeoff discussions, iterating PRs based on maintainer/community feedback
- Incremental, low-risk performance refactors using feature flags plus unit/snapshot tests and performance benchmarks
- Creates developer-friendly docs with minimal quickstart, examples, and enforces doc updates as part of PR review
- Strong user/community support loop: requests minimal repros, profiles issues, ships fixes/workarounds, and follows up to confirm resolution
- Ownership in ambiguous environments: scoped and delivered an LLM-driven pipeline to normalize millions of supply-chain records, cutting defects by 80% and saving 160+ hours/month
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