Professional Overview
MLOps Engineer with 12+ years in software engineering, CI/CD and production AI platforms. I build and operate ML infrastructure end to end: model training and deployment pipelines, feature stores, observability and rollback. Core stack: Python, Docker, Kubernetes, Apache Airflow, MLflow, Terraform, AWS and CI/CD. Recently cut regression time by 60% by rebuilding automated test and release infrastructure for enterprise products. I work best with teams that need a senior engineer to own ML platform reliability and delivery speed. Open to full-time, contract and freelance remote roles at $85/hour.
Areas of Expertise
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
