MLOps Engineering Manager
Tasks
- Build and lead MLOps team
- Choose cloud and MLOps tooling for maintainability and impact
- Contribute to AI and ML community and best practices
- Define MLOps processes and tooling
- Ensure models production ready and observable
- Own deployment and operation of machine learning products
- Partner with engineering and data teams to apply engineering standards
- Productionize batch and online machine learning models
- Promote experimentation testing and monitoring
Perks/Benefits
- Dental insurance
- EV scheme
- Extra festive time off
- Family-friendly benefits
- Personal learning budget
- Private healthcare
- Regular learning days
- Work-from-abroad policy
Skills/Tech-stack
API Monitoring | AWS | Access Management | Airflow | Autoscaling | CI/CD | Data Drift | Data Drift Detection | Data Validation | Docker | Drift Detection | Feature Engineering | Feature Store | Infrastructure as Code | MLflow | Model Evaluation | Model Monitoring | PySpark | Python | Spark | Terraform | “as-code”
Education
N/A
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