Data Scientist - ML Engineering
Tasks
- Architect ML infrastructure end to end
- Deploy ML models to production
- Design CI/CD workflows
- Drive MLOps best practices
- Implement model registry and governance
- Mentor MLOps engineers
- Monitor model drift and trigger retraining
Perks/Benefits
- Collaborative culture
- Flexible work culture
- Global opportunities
- Professional development
- Vibrant community
Skills/Tech-stack
Apache Spark | Azure Databricks | Azure Pipelines | CI/CD | Data Governance | Docker | Drift Detection | Kubernetes | MLflow | Machine Learning | Model Drift | Model Drift Detection | Model Monitoring | Python | Retraining automation
Education
N/A
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