MLOps/DevOps/CloudOps

Design, implement, and maintain CI/CD pipelines for ML and application deployments. Build and manage MLOps frameworks for model training, deployment, monitoring, and retraining. Automate infrastructure provisioning using Infrastructure as Code (IaC). Deploy and manage machine learning models in production environments. Monitor application and model performance, ensuring high availability and reliability. Manage containerized applications using Docker and Kubernetes. Collaborate with Data Scientists, ML Engineers, and Development teams to streamline deployments. Implement security, compliance, and governance best practices across cloud environments. Optimize cloud infrastructure for scalability, performance, and cost efficiency. Troubleshoot production issues and perform root cause analysis.

Python, Information Retrieval, Text Processing, DevOps, CI/CD, Monitoring Docker, Git, MLflow, model serving, monitoring, debugging, version control, CI/CD, Kubernetes Prompt Engineering, AI Coding Assistants