ML Engineer focused on building practical AI systems — from production pipelines to intelligent agents.
- ML Engineering — end-to-end pipelines, feature engineering, model evaluation, MLOps
- AI Systems — LLM-powered agents, RAG pipelines, tool-use workflows
- Automation — content pipelines, API integrations, backend services (FastAPI, Python)
Working through a structured roadmap covering:
- ML & DL depth (stats, optimization, model internals)
- LLMs, fine-tuning, and retrieval systems
- ML systems design and production deployment
Open to ML engineering conversations, consulting, or collaboration.