AI DevOps Engineer

We are seeking an AI DevOps Engineer to design, implement, and maintain scalable infrastructure for machine learning and artificial intelligence systems. The role involves bridging the gap between data science teams and production environments by creating robust CI/CD pipelines, automating model deployment workflows, and ensuring high availability of AI services. You will work closely with ML engineers, data scientists, and software developers to operationalize AI models and optimize compute resources for training and inference workloads. Responsibilities include managing containerized AI applications using Kubernetes and Docker, implementing infrastructure as code with tools like Terraform or CloudFormation, and monitoring system performance using cloud-native observability stacks. You will also be responsible for setting up and maintaining MLOps platforms, managing GPU clusters, and ensuring secure, compliant, and reproducible AI environments. This is an excellent opportunity for a DevOps professional looking to specialize in AI infrastructure and contribute to cutting-edge machine learning projects. The ideal candidate has experience with cloud platforms such as AWS, GCP, or Azure, strong scripting skills in Python and Bash, and a solid understanding of machine learning model lifecycle management.

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