MLOps Engineer (Remote)

Role Overview

Joveo is hiring an MLOps Engineer (Remote) to build and operate the infrastructure that reliably moves machine learning models from experiment to production. You’ll serve as the backbone of the AI delivery pipeline, applying the same rigor to model versioning, monitoring, and deployment as is done for software systems.

Responsibilities

• Build and maintain ML pipelines from training through deployment and monitoring
• Design model registries, experiment tracking, and feature store infrastructure
• Automate model retraining, validation, and deployment workflows
• Monitor deployed models for performance drift, data skew, and prediction quality
• Collaborate with ML engineers and data scientists to streamline path-to-production
• Integrate ML infrastructure with CI/CD systems and cloud platforms

Required Qualifications

• Strong experience with ML platforms such as MLflow, Kubeflow, SageMaker, or Vertex AI
• Proficiency in Python and infrastructure tooling including Docker, Kubernetes, and Terraform
• Experience building automated model training and deployment pipelines
• Familiarity with feature stores such as Feast, Tecton, or Hopsworks
• Understanding of model monitoring and drift detection approaches
• Strong DevOps/platform engineering fundamentals applied to the ML lifecycle