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Jingyi Tian

Junior Machine Learning Engineer specializing in MLOps and LLM/RAG systems

Daxwell, LLCColumbia UniversityHouston, TX2 Years ExperienceJunior LevelWorks On-Site

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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%).

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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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Experience

Machine Learning EngineerDaxwell, LLC · Sep 2024 – Present
Data Analysis InternKantar · Jun 2021 – Sep 2021internship

Education

Columbia Universitymaster, Biostatistics (2024)
Renmin University of Chinabachelor, Statistics (2022)

Awards

  • Delta Pi Chapter membership - Delta Omega Honorary Society in Public Health
  • 3rd Prize - 12th National College Mathematical Competition (Chinese Mathematical Society)

Skills

PythonRSQLTableauXGBoostMachine LearningMLOpsFeature EngineeringAPI DevelopmentPrompt EngineeringSchema ValidationRetrieval-Augmented Generation (RAG)LangChainLangGraphPostgreSQL

Languages

English

Memberships

  • Delta Omega Honorary Society in Public Health

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Jingyi TianJunior Machine Learning Engineer specializing in MLOps and LLM/RAG systems