ML DevOps Engineer

Sourced from activejobs.us

Contract MLOps role supporting Impetus/United Airlines in Chicago, focused on building and maintaining infrastructure and CI/CD pipelines for production machine learning and AI applications. The engineer will automate model training, deployment, and rollback while managing cloud infrastructure, containerized serving, and monitoring for model performance and drift. Requires strong hands-on MLOps, Kubernetes, and cloud experience with production model deployment.

• Build and maintain CI/CD pipelines for ML and AI models
• Automate model training, testing, deployment, and rollback
• Manage cloud infrastructure for ML model hosting and serving
• Containerize applications with Docker and deploy via Kubernetes
• Implement monitoring for model performance, data drift, latency, and cost
• Manage model versioning, experiment tracking, and model registries
• Collaborate with data science and engineering teams
• Ensure security, access control, and compliance
• Troubleshoot production issues and maintain reliable ML operations

• 5+ years overall IT experience, including 3+ years in MLOps or ML-focused DevOps
• Hands-on experience with AWS, Azure, or GCP
• Experience with MLOps tools such as MLflow, Kubeflow, SageMaker, Azure ML, or Databricks
• Strong experience with Docker and Kubernetes
• CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps
• Infrastructure as Code experience (Terraform, CloudFormation, or similar)
• Scripting skills in Python and Bash
• Monitoring tools such as Prometheus, Grafana, Datadog, or CloudWatch
• Understanding of ML lifecycle, model deployment, and production model serving

• Experience with Generative AI / LLM application deployment and model serving
• Knowledge of API gateways
• AWS, Azure, or other relevant cloud certifications
• Experience in regulated industries or large enterprise environments