Senior MLOPs engineer
Tasks
- Collaborate with Data Science, Data Engineering and Architecture teams
- Define engineering standards for ML
- Design pipelines using Databricks
- Ensure efficient, reproducible and secure deployments
- Implement automation and optimization of ML pipelines
- Manage infrastructure for model lifecycle
- Optimize costs and performance in cloud environments
- Provide technical guidance and mentorship in MLOps
Perks/Benefits
- Flexible work options
- Health and wellness programs
- Performance bonuses
- Social and volunteering activities
- Training and certifications
- Vacation and leave policies
Skills/Tech-stack
AWS | Alerts | Azure | Azure DevOps | CI/CD | Databricks | Delta Lake | Docker | GCP | GitHub Actions | Jenkins | Kubernetes | Logging | MLflow | Metrics | Monitoring | Python | SQL | Spark
Education
Roles
Engineer | MLOps Engineer | Senior MLOps | Senior MLOps Engineer
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