Senior AI Platform Engineer
Tasks
- Automate release and versioning for ML workflows
- Build and maintain Kubeflow systems
- Collaborate on data governance and catalog integration
- Design cloud-native AI/ML infrastructure
- Develop internal ML lifecycle APIs and tools
- Implement MLOps workflows for production deployments
- Improve platform reliability scalability and performance
- Standardize CI CD testing and observability
- Support LLMOps lifecycle management
- Translate ML needs into platform architecture
Perks/Benefits
- Career Development Programs
- Continuous learning opportunities
- Dental insurance
- Health insurance
- Home office stipend
- Life insurance
- Paid parental leave
- Paid time off
- Remote work flexible hours
- Therapy sessions
- Wellness platform membership
Skills/Tech-stack
APIs | Amazon Web Services | Apache Spark | Automation | CI/CD | Infrastructure as Code | Kubeflow | Kubernetes | LLMOps | MLOps | Observability | Python | Terraform | Web Services | “as-code”
Education
N/A
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