Full Stack engineer pivoting to ML Systems & AI Infrastructure. I like building things that don't break — distributed AWS pipelines, live Kubernetes anomaly detectors, and voice-driven RAG agents.
- 🎓 MS Computer Science · Arizona State University
- 🔭 Building: distributed systems, LLM-powered tools, Go backends
- 📖 Currently learning: Triton, CUDA, LLM inference internals
- 🤝 Open to: ML Systems, AI Infrastructure, Full Stack roles & internships
Languages
Frontend & Backend
Cloud & Infra
ML / Data
scikit-learn · pandas · Triton (learning)
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Voice-driven RAG agent with real-time speech processing and LLM orchestration pipelines.
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High-performance in-memory data store built from scratch in Go with RESP protocol support.
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Fault-tolerant P2P file storage with custom TCP networking and concurrent data streaming in Go.
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Full-stack learning platform with interactive course management and real-time features.
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🔒 Private Projects
| Project | Stack | Highlight |
|---|---|---|
| 🔍 K8s Log Anomaly Detection | LSTM · LightGBM · Kubernetes | 95% accuracy on cluster anomaly detection |
| 📡 Distributed Face Recognition | AWS EC2 · SQS · S3 · DynamoDB | Custom autoscaler + distributed pipeline |
