Melbourne | ML Engineer | Nature-published Astrophysicist

Astrophysics PhD turned ML Engineer. I build production ML systems—embeddings, vector search, voice agents, autonomous coding systems. My background is Bayesian inference and statistical modeling, now applied to real-world engineering problems.

• Mycelium – Open-source architecture for autonomous coding agents (24+ hour unattended runs)
• FAANGmatch – Job matching platform indexing 15,000+ roles across top tech companies

• First-author paper in Nature Astronomy (top 0.03% citations)

ML/AI: PyTorch, FAISS, Transformers, Bayesian inference, RAG
Infrastructure: AWS (EC2, Lambda, Beanstalk), GCP, Terraform, Docker
Backend: FastAPI, Python
MLOps: GitHub Actions, model monitoring, inference optimization

PhD Astrophysics @ University of Melbourne | Stanford XCS234 Reinforcement Learning