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JT
Jingyi Tian
Junior Machine Learning Engineer specializing in MLOps and LLM/RAG systems
Houston, TXMachine Learning Engineer2 years experienceJuniorTransportation & LogisticsTechnologyMarket Research
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About
LLM/agentic workflow builder focused on productionizing document-processing systems. Redesigned pipelines with LangGraph + RAG, schema-aware validation, and eval/monitoring loops; known for fast incident diagnosis (restored accuracy from ~70% to >95% same day). Partners closely with sales and stakeholders to deliver tailored demos and drive adoption (reported +40%).
Experience
Machine Learning EngineerDaxwell, LLC
Data Analysis InternKantar
Education
Columbia Universitymaster, Biostatistics (2024)
Renmin University of Chinabachelor, Statistics (2022)
Key Strengths
- Took LLM document-processing prototype to production with focus on reliability and scale
- Rapid stakeholder iteration via frequent demos and feedback loops to validate edge cases
- Production troubleshooting using structured logging, prompt/version tracing, and replaying failed inputs
- Recovered workflow accuracy from ~70% to >95% in one day by fixing preprocessing/retrieval and adding validation/retries
- Strong technical communication: delivers developer-focused demos/workshops with architecture, trade-offs, failure cases, and code walkthroughs
- Sales partnership: builds tailored demos/prototypes and benchmarks to address accuracy/latency concerns and drive adoption (+40%)
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