Description

You will build and maintain production-grade machine learning systems, focusing on scalability and reliability beyond initial experimentation.

This role is remote.

Responsibilities

• Deliver production-grade ML pipelines and enterprise-scale solutions.
• Build and manage CI/CD pipelines for ML models in Kubernetes.
• Implement model monitoring, retraining loops, and version governance.
• Maintain robust infrastructure for cloud-based ML deployments.

Required Skills

• 5+ years of professional experience in ML engineering.
• Strong Python engineering background.
• Hands-on experience with MLflow, Kubeflow, and/or Airflow.
• Experience building CI/CD pipelines in Kubernetes environments.
• Experience with AWS, GCP, or Azure for cloud ML deployments.
• Familiarity with energy-industry data (time-series, forecasting, optimization, asset monitoring).

Preferred Skills

• Experience supporting ML systems in energy, utilities, oil & gas, renewables, or power trading.
• Understanding of compliance, reliability, and safety requirements in energy operations.

Key Skills

Education

Any Gradute