AI / ML Engineer β Generative AI Β· Machine Learning Β· Computer Vision π Master of Applied AI (Deakin University) Β· π Geelong, Australia
I build and ship ML systems end-to-end β from real-time computer vision on edge GPUs to agentic, RAG-based LLM applications with LLMOps tooling. Currently focused on production GenAI.
- π Building a public GenAI portfolio β RAG, agentic AI, and LLMOps
- π± Going deeper on LangGraph agents, RAG evaluation, and MLOps
- π¬ Ask me about computer vision on NVIDIA Jetson, RAG pipelines, or LLM apps
- π Open to mid-level GenAI / ML / MLOps roles in Australia (full working rights)
| Project | What it is | Stack |
|---|---|---|
| ai-job-assistant-v2 π§ | End-to-end agentic job-search assistant β resume parsing with HITL review, job search & LLM reranking, gap analysis, grounded resume/cover-letter tailoring, agent+tools orchestration, and an MCP server, fully traced | FastAPI Β· LangGraph Β· OpenAI Β· Langfuse Β· MCP Β· PostgreSQL Β· Docker Β· Azure |
| pdf-rag | Grounded PDF RAG chatbot with anti-hallucination retrieval & multi-turn chat | LangChain Β· Chroma Β· sentence-transformers Β· gpt-4o-mini Β· Streamlit Β· Docker |
| pytorch-transformer | A Transformer built from scratch ("Attention Is All You Need") | PyTorch Β· Docker |
π§ = in active development
GenAI / LLM
Also: LangGraph (agentic) Β· RAG (hybrid retrieval) Β· Chroma (vector DB) Β· Langfuse (tracing) Β· MCP Β· prompt engineering
Machine Learning / Deep Learning
Computer Vision / Edge
Also: TensorRT Β· TFLite Β· YOLOv5 Β· MobileNet Β· MIDAS
Cloud & Tools
- π₯ Winner β Intel Ultimate Coder Challenge ($22,400)
- π₯ Winner β Eclipse Open IoT Challenge ($5,000 USD)
- π€ Shipped real-time perception (depth, VIO, pose) on NVIDIA Jetson β demoed at Avalon Airshow 2023