Senior Machine Learning Ops Engineer
Tasks
- Build and maintain containerized model serving solutions
- Design deploy maintain scalable ML infrastructure for training batch inference real time inference
- Document architecture deployment standards and operational processes
- Establish observability and monitoring for ML systems drift detection data quality monitoring and alerting
- Implement CI/CD Infrastructure-as-Code testing and deployment automation
- Optimize reliability scalability governance and operational efficiency for ML workflows
- Productionize ML models with Data Science and Data Engineering teams
- Provision deploy infrastructure and services using Infrastructure-as-Code
Perks/Benefits
Skills/Tech-stack
AWS | Airflow | Arize | Bash | BigQuery | CI/CD | CloudFormation | Dagster | Databricks | Django | Docker | Drift Detection | ECS | EKS | Evidently | FastAPI | Feature Store | Flask | Infrastructure as Code | Kubernetes | MLflow | Model Drift | Model Drift Detection | Model Monitoring | Monte Carlo | OpenTofu | Prefect | Pytest | Python | SQL | Snowflake | Terraform | Unix | WhyLabs | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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