What are the responsibilities and job description for the MLOPs Engineer position at DynPro, Inc.?
Job Description:
We are seeking an ML Ops 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.
- ML Ops Support:
- 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.
- 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
- Advanced Python, Docker, Linux administration, GitHub Actions, Azure
