MLOps Engineer

Job Overview:
We are hiring an MLOps Engineer to build and operate the infrastructure that takes Joveo's machine learning models from experiment to production reliably and repeatedly. You will be the backbone of our AI delivery pipeline — ensuring models are versioned, monitored, and deployed with the same rigour as our software systems.

Duties and 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 the path to production
- Integrate ML infrastructure with CI/CD systems and cloud platforms

Required Qualifications:
- Strong experience with ML platforms — 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 tools and drift detection approaches
- Strong DevOps/platform engineering fundamentals applied to the ML lifecycle

Additional Notes:
Joveo is an equal opportunity employer. We are committed to building an inclusive workplace and welcome applications from all qualified individuals regardless of race, color, ethnicity, nationality, gender, gender identity or expression, sexual orientation, age, religion, disability, marital status, or any other characteristic protected by applicable law. All hiring decisions are made solely on the basis of qualifications, skills, and demonstrated ability.