Platform Engineer (Cloud-Native AI/ML Systems Integration)
Tasks
- Architect Kubernetes platforms for AI ML workloads
- Build and enhance CI/CD pipelines
- Build and manage containerized environments
- Collaborate to translate requirements into deployable systems
- Configure data pipelines for ingestion transformation and model lifecycle
- Implement Infrastructure as Code with Terraform and Ansible
- Implement monitoring and observability with Prometheus and Grafana
- Integrate AI ML services into secure systems
- Operate Kubernetes platforms
- Support engineering in classified constrained environments
Perks/Benefits
- 401k match
- Home office and equipment plan
- Industry leading pay schedule
- Life insurance
- Long-term disability
- Medical, dental, and vision coverage
- Paid certifications and professional development
- Paid time off
- Short-term disability
Skills/Tech-stack
Ansible | CI/CD | Cloud Native | Cloud-native technologies | Data Pipelines | DevSecOps | Distributed Systems | Docker | GitHub Actions | GitLab | Grafana | Helm | Infrastructure as Code | Jenkins | Kubernetes | Machine Learning | Machine Learning Operations | Machine Learning Operations MLOps | Native technologies | OCI | Observability | Prometheus | Terraform | “as-code”
Education
N/A
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