AI DevOps Engineer

This AI DevOps Engineer role focuses on bridging the gap between artificial intelligence/ML development and operations, enabling seamless deployment, scaling, and monitoring of AI systems in production environments. You will work with cross-functional teams including data scientists, ML engineers, and software developers to build and maintain robust CI/CD pipelines tailored for machine learning workloads, manage cloud infrastructure for AI deployments, and implement monitoring solutions to track model performance and system reliability. The position offers a competitive annual salary range of $140,000 to $175,000, with full-time employment terms. Ideal for professionals who enjoy turning machine learning research and prototypes into production-ready, high-impact solutions, this role spans a wide range of industries including technology, finance, healthcare, and retail. You will have the opportunity to work on cutting-edge AI projects, optimize deployment workflows for scalability and cost-efficiency, and ensure compliance with security and governance standards for AI systems.

• 3+ years of professional DevOps engineering experience, with prior work supporting AI/ML workloads preferred
• Proficiency in cloud platforms (AWS, Azure, or GCP) and infrastructure-as-code tools such as Terraform or CloudFormation
• Hands-on experience with CI/CD tools (Jenkins, GitLab CI, GitHub Actions) and containerization/orchestration technologies (Docker, Kubernetes)
• Familiarity with MLOps tools (MLflow, Kubeflow, Vertex AI) and machine learning model deployment best practices
• Strong scripting capabilities in Python, Bash, or similar languages, plus experience with monitoring and logging tools (Prometheus, Grafana, ELK Stack)
• Understanding of the full AI model lifecycle, including versioning, testing, performance monitoring, and retraining workflows
• Excellent cross-functional collaboration skills to work with data science, engineering, and product teams