About the role

Role Overview

Joveo AI is hiring an MLOps Engineer (Remote) to build and operate the infrastructure that takes ML models from experiment to production reliably and repeatedly. You will own the backbone of the AI delivery pipeline, ensuring models are versioned, monitored, and deployed with software-engineering rigor.

Responsibilities

Build and maintain ML pipelines from training to 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

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

Nice-to-Haves

Not explicitly stated.

About Joveo AI

Joveo AI operates an AI-first recruitment advertising platform that uses machine learning, real-time bidding, and predictive analytics to drive hiring decisions. The company helps large employers find the right candidates faster and more fairly by running large-scale ML systems in production.