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+# CV -- Alex Chen
+
+**Location:** Austin, TX
+**Email:** alex@example.com
+**LinkedIn:** linkedin.com/in/alexchen
+**Portfolio:** alexchen.dev
+**GitHub:** github.com/alexchen
+
+## Professional Summary
+
+Full-stack AI engineer with 6 years building production ML systems. Led the ML platform at a Series B fintech (2020-2024), scaling from 2 models to 15+ in production. Built real-time fraud detection (99.7% precision, $2M/year saved), recommendation engine (18% uplift), and an internal MLOps platform serving 4 engineering teams.
+
+## Work Experience
+
+### TechFin Corp -- Austin, TX
+
+**Senior ML Engineer / ML Platform Lead**
+2020-2024
+
+- Led ML platform team (3 engineers), built internal MLOps tooling: model registry, A/B testing framework, feature store
+- Designed real-time fraud detection pipeline: Kafka → feature computation → model inference → decision engine. 99.7% precision at 50ms p99
+- Built recommendation engine for lending products: collaborative filtering + LLM reranking. 18% conversion uplift
+- Reduced model deployment time from 2 weeks to 4 hours with CI/CD pipeline (GitHub Actions + SageMaker)
+- Established model monitoring: drift detection, performance dashboards (Grafana), automated retraining triggers
+
+### DataStartup Inc -- Remote
+
+**ML Engineer**
+2018-2020
+
+- Built NLP pipeline for document classification (BERT fine-tuning, 94% accuracy on legal docs)
+- Implemented search ranking with learning-to-rank models
+- Set up experiment tracking with MLflow and model versioning
+
+## Projects
+
+- **FraudShield** (Open Source) -- Real-time fraud detection framework. Kafka Streams + feature store + model serving. 500+ GitHub stars
+- **LLM Eval Toolkit** (Open Source) -- Evaluation framework for LLM applications. Supports custom metrics, regression testing, CI integration
+
+## Education
+
+- MS Computer Science, UT Austin (2018)
+- BS Computer Science, UC Berkeley (2016)
+
+## Skills
+
+- **ML/AI:** PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain
+- **MLOps:** SageMaker, MLflow, Kubeflow, Airflow, Feature Store
+- **Infra:** Kubernetes, Kafka, Redis, PostgreSQL, AWS
+- **Languages:** Python, Go, TypeScript, SQL