Software Development Engineer - ML Ops
Tasks
- Apply Kubernetes and Docker for ML runtime inference
- Automate operational processes and enable engineer self service
- Build and operate distributed systems
- Deploy and orchestrate containers in production
- Design document test and debug software components
- Develop automation frameworks and tooling
- Implement CI/CD pipelines
- Manage infrastructure as code
- Provide rotational on-call support
- Research evaluate and adopt ML tools with reliability and scale
Perks/Benefits
Skills/Tech-stack
AWS | ArgoCD | CI/CD | Distributed Systems | Docker | GCP | Git | Grafana | Infrastructure as Code | Jenkins | Kubernetes | Microservices | Monitoring | Python | REST | Service Mesh | Service Oriented | Service-Oriented Architecture | Terraform | “as-code”
Education
Roles
DevOps | DevOps Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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