Full-Stack → ML Engineer

I build end-to-end systems and now focus on applied machine learning and production ML.

4 ML ProjectsMetrics-drivenProduction mindsetPython / PyTorch / SklearnDeployment experience

Transition Story

tabularchurnproduction

Predicting which customers are likely to churn for a SaaS platform.

Approach: Baseline: Logistic Regression → XGBoost → Feature selection → SHAP analysis.Key Metric: AUC: 0.89, Precision@Top10%: 0.72

nlpclassificationbert

Automated routing of support tickets using NLP classification.

Approach: Baseline: TF-IDF + Logistic Regression → fine-tuned BERT → error analysis.Key Metric: Macro F1: 0.81, Routing accuracy: 92%

time-seriesforecastinglstm

Forecasting hourly energy demand for a utility provider.

Approach: Baseline: ARIMA → LSTM → Feature engineering → Hyperparameter tuning.Key Metric: MAE: 0.13, RMSE: 0.21

ragllmretrieval

Retrieval-Augmented Generation for internal knowledge base Q&A.

Approach: Baseline: BM25 → Dense retrieval → OpenAI GPT-3.5 → RAG pipeline.Key Metric: Top-1 accuracy: 84%, Mean reciprocal rank: 0.78