ML Ops Enigneer / 1
Summary
Build and maintain ML infrastructure: automate CI/CD-driven deployments, orchestrate scoring pipelines, and manage model versioning and monitoring with MLflow and Databricks.
- Automate resource provisioning and deployments from CI CD pipelines
- Collaborate with DevOps for shared storage and Delta Lake
- Deploy machine learning models using MLflow
- Ensure fault tolerance and job restart
- Implement infrastructure as code for governance
- Implement model version control and tracking
- Integrate logging monitoring and alerting dashboards
- Monitor model performance and scoring metrics
- Orchestrate ML scoring pipelines
- Set up Databricks clusters jobs and workflows
Perks/Benefits:
- Cafeteria benefits
- Charity initiatives
- Conference participation
- Flexible working hours
- Hybrid work
- Sports programs
- Supportive inclusive culture
- Team-building budget
- Training funding