MS in Data Science @ Columbia University
I build AI systems that move from research prototypes to scalable, production-ready applications.
My work spans model training pipelines, backend infrastructure, distributed workers, and polished front-end interfaces that deliver ML to real users.
- End-to-end ML systems: training, evaluation, inference, and deployment
- Backend + distributed infrastructure: APIs, async workers, pipelines, queues
- Full-stack tools: React/Next.js dashboards for real-world workflows
- Applied AI products: tools used by students, debate teams, and professionals
ML & AI
PyTorch Tensorflow Transformers LoRA scikit-learn OpenAI API NLP Model Training
Backend & Systems
FastAPI Node.js TypeScript Async Workers Docker REST Supabase
Frontend
React Next.js TypeScript TailwindCSS
Infra & Tooling
Docker Git Queues Vercel Supabase Render
- Building agent workflows that automate open-ended tasks
- Efficient finetuning pipelines for real-world applied use cases
- ML engineering in finance and markets
Website: https://darief.com
LinkedIn: https://linkedin.com/in/dariefmaes