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Alicia Geng
Entry-level AI/ML Engineer specializing in AWS MLOps and computer vision
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Built and shipped a production RAG question-answering system using LangChain/OpenAI, Docker, and FastAPI, then reduced hallucinations through disciplined retrieval tuning and constrained prompting. Also implemented a custom evaluation framework (QA-pair dataset) to measure faithfulness/relevance and deployed containerized ML microservices on AWS ECS/Fargate with ALB and rolling, zero-downtime updates.
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Key Strengths
- Built and deployed a production RAG system (LangChain + OpenAI) exposed via FastAPI and Docker
- Systematic hallucination reduction via retrieval parameter tuning (e.g., ~500-token chunks, ~10% overlap) and constrained prompting
- Designed a custom QA-pair evaluation dataset/framework to benchmark faithfulness and answer relevance
- Production orchestration on AWS ECS/Fargate with ALB traffic distribution and rolling updates for zero-downtime deployments
- Experience containerizing models into independent microservices for scalable deployment
- Collaborated directly with startup founder to translate business/customer needs into an initial ML model using early client historical data
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