Description

Deploy, monitor, and maintain machine learning models in production environments.

This role is remote.

Responsibilities

• Design and deploy scalable ML pipelines using Kubeflow and Airflow.
• Develop and maintain reliable CI/CD pipelines for code and model deployment.
• Deploy and monitor ML models using TensorFlow Serving, Prometheus, and Grafana.
• Integrate and manage model versioning and experiment tracking with MLflow.
• Implement DevOps practices to streamline the software development lifecycle.

Required Skills

• 3–5 years of experience in MLOps, DevOps, or software development.
• Strong understanding of containerization (Docker, Kubernetes).
• Proficiency in Python or Bash scripting.
• Experience with CI/CD tools like Jenkins or GitLab CI.
• Expertise in cloud platforms (AWS, Azure, or GCP).
• Familiarity with ML pipeline tools (Kubeflow, Airflow, MLflow).
• Knowledge of monitoring tools (Prometheus, Grafana).
• Experience with Terraform for infrastructure provisioning.
• Working knowledge of TensorFlow.

Key Skills

Education

Any Graduate