University of Pennsylvania
ML Research Engineer
- Built responsive React dashboards and versioned TypeScript REST APIs with Zod validation, rate limiting, and OpenAPI documentation, surfacing ML enrollment insights across Penn's 12 academic schools for 3 downstream teams.
- Fine-tuned a BERT-based classifier on 50K labeled enrollment records with HuggingFace Transformers, reaching 84% held-out accuracy with cross-validation and hyperparameter tuning.
- Stood up an MLflow pipeline with a model registry, retraining triggers, and a versioned serving API; rewrote batch inference with asyncio concurrency for a 6x throughput gain at identical accuracy.
- Added SHAP feature importance, early stopping, and calibrated probability outputs to every deployed model, and set up GitHub Actions CI enforcing type-safety, lint, and test coverage on every pull request.
PythonPyTorchHuggingFaceMLflowReactTypeScriptasyncio