About the role

Role Overview

Joveo AI is hiring an MLOps Engineer (Remote) to build and operate the infrastructure that reliably moves machine learning models from experiment to production. You’ll help ensure models are versioned, monitored, and deployed with software-engineering rigor.

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

Required Skills & Qualifications

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

Nice to Have

Experience spanning the full ML lifecycle: experimentation, productionization, monitoring, and retraining

About Joveo AI

Joveo AI is a technology company building an AI-first recruitment advertising platform. It uses machine learning, real-time bidding, and predictive analytics to help major employers make faster and fairer hiring decisions. The platform runs large-scale ML infrastructure to take models from experimentation to production.