MLOps Engineer
We are seeking an MLOps Engineer to support machine learning deployment and infrastructure needs for a hybrid contract position in San Francisco, CA. This role focuses on managing ML Ops and Airflow platforms to empower Data Science and Engineering teams.
Responsibilities:
• Assist in developing and deploying ML models (transitioning from AWS Sagemaker to DataRobot).
• Manage AWS infrastructure, CI/CD pipelines, and Python-based components.
• Airflow Platform Support:
• Administer and support AWS MWAA-hosted Airflow.
• Create/manage secrets, deploy DAGs, review workflow modifications, and ensure best practices.
Required Skills:
• Python: 4+ years of experience
• REST APIs: 2+ years
• Airflow: 3+ years (DAG authoring, deployment, administration)
• AWS Infrastructure: 4+ years (e.g., S3, Sagemaker, MWAA, ECS, SecretsManager)
• Terraform: 1+ year
Bonus Skills:
• Advanced Python, Docker, Linux administration, GitHub Actions, Azure
Regards,
Gaganpreet Singh
Senior Talent Executive
