Building scalable intelligent systems and robust data infrastructure.
I operate at the intersection of Machine Learning and DevOps, ensuring that models don't just stay in notebooks but drive value in production.
- End-to-End Pipelines β Architecting workflows from data ingestion to model deployment.
- Infrastructure Automation β Containerization (Docker), Orchestration, and CI/CD workflows.
- Model Observability β Monitoring drift, performance, and reliability in real-time.
- Data Cleaning & ETL β Transforming messy raw data (CSV/Excel/JSON) into analysis-ready formats using Pandas.
- Workflow Automation β Writing robust Python scripts to automate reporting, scraping, and daily tasks.
- Database Management β Designing schemas and managing data flow into PostgreSQL.
| Domain | Tools & Technologies |
|---|---|
| Languages | Python, SQL, Bash |
| Data Engineering | Pandas, NumPy, PostgreSQL, Apache Airflow |
| Infrastructure | Docker, Kubernetes, AWS, Linux |
| CI/CD & DevOps | GitHub Actions, Jenkins, Git |
| ML & Serving | Scikit-Learn, MLflow, FastAPI, Ray Serve |
| Observability | Prometheus, Grafana, Evidently AI |
I am open to MLOps collaborations and Data Engineering contracts.
- Email: [email protected]
- GitHub: github.com/JesFusion
