I bridge the gap between autonomous deep learning systems and high-performance backend pipelines.
I am an engineer specializing in AI/ML systems and backend development. My work focuses on training specialized transformer architectures and designing high-performance backend pipelines. I construct low-level performance systems and concurrent backend frameworks.
Highlights
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cancer_pred_model
cancer_pred_model PublicEnd-to-end chest CT scan cancer classification using VGG16 (TensorFlow/Keras). Features a DVC-orchestrated 4-stage pipeline (ingestion → base model → training → evaluation), MLflow experiment track…
Python
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protask
protask PublicProduction-ready task management boilerplate Go (Echo v4) REST API with PostgreSQL, Redis/Asynq queues, Clerk auth & New Relic APM, paired with a React SPA (Vite + Tailwind CSS v4). Type-safe contr…
TypeScript
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fraud-detection-optimization
fraud-detection-optimization PublicEnd-to-End Fraud Detection Pipeline with LightGBM, Optuna, Simulated Annealing & MLflow
Python
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RedrobRanker
RedrobRanker PublicA CPU-optimized, 11-stage progressive AI candidate discovery and ranking engine. Integrates hybrid lexical (Weighted BM25) & semantic vector retrieval (FAISS), real-time behavioural signal modeling…
Python
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NetSure
NetSure PublicModular, production-ready NIDS pipeline on CICIDS2017 using DVC for orchestration, MLflow for experiment tracking, and Docker for containerized deployment. Features hyperparameter-optimized XGBoost…
Jupyter Notebook
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