I am a Senior Machine Learning Engineer with 14+ years of experience building production AI systems that solve real business problems. My work has focused on GenAI, LLM inference, multi-agent architectures, RAG pipelines, and applied machine learning in regulated environments.

I have spent much of my career working at the intersection of advanced ML and strong engineering discipline. I care about shipping systems that are reliable, observable, secure, and maintainable, not just impressive in demos.

My background includes healthcare, fintech, fraud detection, and lending compliance. I have built solutions that support clinical triage, credit underwriting, and real-time fraud detection, with a strong emphasis on safety, explainability, and operational readiness.

I own the full stack of ML delivery, from model selection and fine-tuning through API design, MLOps, deployment, and production monitoring. I am comfortable working across Python, AWS, Docker, Kubernetes, Terraform, and modern LLM tooling.

I enjoy designing systems that are privacy-conscious and production-ready, including offline and local-first architectures. I have experience building secure, auditable workflows with strict validation and traceability requirements.

I work well independently, communicate clearly across technical and non-technical teams, and I am looking for a remote-first role where I can contribute meaningful work on challenging AI systems.