Senior MLOps Engineer
Tasks
- Build CI CD pipelines for machine learning workflows
- Collaborate on model productionization with data science and engineering
- Design machine learning deployment platforms
- Develop scalable machine learning infrastructure and pipelines
- Ensure secure reliable scalable infrastructure
- Implement model monitoring and observability
- Improve platform performance efficiency and usability
- Lead model governance versioning testing and validation
- Mentor team members on MLOps best practices
Perks/Benefits
- 401k
- Caregiving benefits
- Fertility benefits
- Health insurance
- Life insurance
- Long-term disability
- Mental health resources
- Paid sick leave
- Parental leave
- Short-term disability
- Tuition assistance
- Vacation policy
- Wellness benefits
Skills/Tech-stack
AWS | Alerting | Azure | CI/CD | Cloud platform | Docker | Experiment tracking | FastAPI | GitHub Actions | Google Cloud | Google Cloud Platform | Infrastructure as Code | Jenkins | Kubeflow | Kubernetes | Logging | ML model monitoring | MLflow | Model Monitoring | Model version control | Python | TensorFlow Serving | Terraform | Torchserve | Version control | Weights and Biases | “as-code”
Education
N/A
Roles
Engineer | ML Engineer | MLOps Engineer | Senior MLOps | Senior MLOps Engineer
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