ML Ops Engineer

Luminary Cloud is seeking an experienced ML Ops Engineer to build and maintain robust MLOps infrastructure for our Physics AI platform. The ideal candidate will have 5+ years of industry experience in MLOps, including model development, deployment, monitoring, and scaling ML systems in production environments.

Requirements

• Bachelor's degree or higher in Computer Science, Data Science, Statistics, Applied Mathematics, or related fields.
• 5+ years of industry experience in machine learning operations (MLOps)
• Proficiency in Python with demonstrated experience writing production-level code
• Solid experience with Google Cloud Platform (GCP), Docker, Kubernetes, and Vertex AI for cloud-based ML infrastructure
• Hands-on experience with modern MLOps frameworks including Kubeflow, MLflow, and Argo Workflows
• Strong experience building scalable data pipelines, particularly with large volumes of unstructured data and familiarity with VTK for 3D geometric data
• Proven ability to independently deploy ML models and set up inference pipelines with monitoring capabilities
• Experience managing model registries and integrating them with automated workflows
• Strong problem-solving skills and ability to troubleshoot complex distributed systems