# 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
