Backend Engineer · Project10X Architect · ML Systems
I build backend-first systems with a bias for clean API surfaces, async workflows, and data-driven pipelines. My learning model is Project10X — a disciplined, project-centric framework that converts mathematical insight and algorithmic rigor into deployable prototypes.
View Stack
- Languages: Python, JavaScript/TypeScript, Java, C++
- Backend: FastAPI, SQLModel, Django, DRF, Celery, Redis
- Auth & APIs: OAuth2, JWT, httpx, BackgroundTasks, async orchestration
- Databases: PostgreSQL, SQLite, MySQL
- ML & Data: NumPy, Pandas, Scikit-learn, Matplotlib
- Frontend: React (Vite), Tailwind, Chakra UI
- DevOps & Tools: Docker, Docker Compose, Git, Linux (WSL), Render, Vercel
- Testing: pytest, unittest, APIClient, E2E patterns
| Domain | Current Stage | Status |
|---|---|---|
| FastAPI Backend | Dockerized production API | ✅ Completed |
| Linear Algebra | MatrixOps engine, basis tools | Active |
| Statistics / Probability | Distribution simulators, PMF/PDF overlays | Active |
| Calculus | Limits → derivatives → integrals | Active |
| ML Models | Regression stack + GD variants | Active |
Project10X enforces iteration, edge-case reasoning, and production-level expectations across 10 progressive projects per domain.
Execution Priorities
- Engineering backend prototypes and API-driven systems optimized for hackathons
- Joining and actively competing in hackathons to pressure-test architecture, velocity, and teamwork
- Developing math-grounded ML pipelines aligned with startup-grade systems
- Exploring simulation engines, async job systems, and model-wrapping APIs
- Preparing for internships with a backend + ML systems emphasis
Email: rmvilla987@gmail.com
LinkedIn: https://www.linkedin.com/in/rmvilla
“I solve real problems today so I can build something that matters tomorrow.”