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Xiaoai Zhu
Entry-level Software Engineer specializing in AI and full-stack data systems
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Backend/AI engineer who has built an offline, citation-grounded RAG system end-to-end with hybrid retrieval, local LLM inference, and quantitative evaluation via RAGAS. Also brings real-time systems experience from an Airbnb-like booking platform and data pipeline/ML quality work from a Bilibili internship, with a strong emphasis on reliability, privacy, and measurable correctness.
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Key Strengths
- End-to-end ownership of backend systems from architecture to deployment
- Strong retrieval and RAG architecture design
- Builds cost-sensitive, privacy-sensitive AI systems with local inference
- Quantitative evaluation mindset using RAGAS for retrieval precision and faithfulness
- Thoughtful tradeoff analysis across latency, reliability, scalability, and developer velocity
- Real-time backend design with WebSockets, Django Channels, and Redis Pub/Sub
- Delivered sub-100ms message delivery for booking-related messaging flows
- Methodical execution in ambiguous early-stage projects through staged scoping and validation
- Data quality and silent-failure detection in ETL and ML pipelines
- Improved classification stability by automating domain-specific stopword updates
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