Description

You will design and implement scalable MLOps architectures to support production machine learning workloads.

Responsibilities

• Design scalable MLOps architectures for production environments.
• Build and manage open-source ML pipelines.
• Support and optimize production ML workloads.
• Integrate DevOps practices into machine learning lifecycles.

Required Skills

• 5+ years of professional experience in architecture and deployment.
• Deep DevOps background with hands-on experience in CI/CD.
• Expertise in AWS SageMaker deployments.
• Experience with open-source ML pipelines such as MLflow or Airflow.
• Proficiency in Python.
• Strong experience with Docker and Kubernetes.
• Proven expertise in architecture design and deployment.

Key Skills

Education

Any Graduate