MLOps Engineer (Remote)

Role Overview

Joveo is hiring an MLOps Engineer (Remote) to build and operate the infrastructure that moves machine learning models from experiment to production reliably and repeatedly. You will be a backbone for Joveo’s AI delivery pipeline, applying the same rigor to model delivery 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 issues
• Collaborate with ML engineers and data scientists to streamline time-to-production
• Integrate ML infrastructure with CI/CD systems and cloud platforms

Required Skills & Qualifications

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

Nice-to-Haves

• None explicitly stated (role lists multiple tools/platforms as qualification areas).