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Gly Vu
Junior Software Engineer specializing in full-stack tools and LLM inference infrastructure
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About
Full-stack/edge-focused engineer who took a manual, terminal-based AI calibration workflow and turned it into a web-enabled remote calibration system designed for low-bandwidth 5G field deployments, now used across 85+ field sites. Experienced operating edge fleets with versioned rollouts, Kubernetes-based cloud monitoring, and Prometheus/Grafana observability, plus refactoring fast-moving AI codebases for modularity and strong typing.
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Key Strengths
- Owned and shipped end-to-end remote calibration system deployed to 85+ field sites
- Strong edge/field systems thinking (designing for poor connectivity and bandwidth constraints)
- Scalable architecture decisions (local processing on edge vs cloud scaling)
- Iterative delivery with stakeholder requirement discovery and frequent demos
- Designed performant data model using DynamoDB PK/SK for fast retrieval
- Built production observability with Prometheus + Grafana and automated health checks
- Improved team velocity via refactoring for modularity, clear interfaces, and typing standards
- Concurrency problem-solving (multiprocessing and state synchronization)
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