MLOps Engineer (Remote)

Role Overview

Joveo is hiring an MLOps Engineer to build and operate the infrastructure that moves Joveo’s machine learning models from experiment to production reliably and repeatedly. You’ll be a core part of the AI delivery pipeline, treating model lifecycle practices with the same rigor as software engineering.

Key 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 delivery to production
• Integrate ML infrastructure with CI/CD systems and cloud platforms

Required Skills & Qualifications

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

Nice to Have

• Broader experience across multiple MLOps/ML platform and feature store ecosystems