Site Reliability Engineer — ML Infrastructure
Tasks
- Apply SRE discipline to ML infrastructure
- Build and maintain CI/CD pipelines
- Build infrastructure as code
- Collaborate with data scientists to operationalize ML models
- Contribute infrastructure for ML workloads on Kubernetes and AWS
- Ensure system reliability, performance, and scalability
- Handle incidents and conduct postmortems
- Implement DevOps methodologies
- Improve ML model deployment pipelines
- Maintain 24 7 Kubernetes production environment
- Manage and evolve AWS infrastructure
- Monitor ML model performance and build alerting and observability
- Proactive system monitoring and configuration
Perks/Benefits
Skills/Tech-stack
Amazon Web Services | ArgoCD | Bash | CI/CD | CloudFront | EC2 | EKS | Fargate | Grafana | Helm | Infrastructure as Code | JavaScript | Kafka | Kubernetes | Lambda | MLOps | MongoDB | PostgreSQL | Prometheus | Python | RDS | S3 | Terraform | Web Services | YAML | “as-code”
Education
N/A
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