MLOps Engineer
We are looking for an ML Ops Engineer to support machine learning deployment and infrastructure management for a hybrid contract position in San Francisco, CA. This role involves managing ML Ops and Airflow platforms, ensuring seamless integration and scalability for Data Science and Engineering teams.
Responsibilities
• ML Ops & Model Deployment
• Assist in the development and deployment of ML models, transitioning from AWS SageMaker to DataRobot.
• Manage AWS infrastructure, CI/CD pipelines, and Python-based components.
• Airflow Platform Management
• Administer and support AWS MWAA-hosted Airflow.
• Manage secrets, deploy DAGs, review workflow modifications, and ensure best practices are followed.
Required Skills
• Python – 4+ years
• REST APIs – 2+ years
• Airflow – 3+ years (DAG authoring, deployment, administration)
• AWS Infrastructure – 4+ years (S3, SageMaker, MWAA, ECS, Secrets Manager)
• Terraform – 1+ year
Preferred Skills
• Advanced Python programming
• Docker and Linux administration
• GitHub Actions
• Azure experience
Regards,
Gaganpreet Singh
Senior Talent Executive
