Innovative and results-driven AI & DevOps Engineer with a strong foundation in automating infrastructure, deploying scalable machine learning systems, and optimizing CI/CD pipelines. With over [X] years of hands-on experience in cloud-native environments (AWS, Azure, GCP), I specialize in bridging the gap between data science and engineering by streamlining model deployment, monitoring, and lifecycle management.
Proficient in Python, Docker, Kubernetes, and Terraform, with deep knowledge of MLOps tools like MLflow, Airflow, and Kubeflow. Passionate about building reliable, reproducible, and secure AI workflows, from research to production. I believe in continuous integration, infrastructure as code, and delivering real-time AI solutions at scale.
Looking to collaborate with forward-thinking teams to automate and accelerate the journey from data to decision.