Senior MLOps Engineer - SRE | DevOps
Remote job
R
A USD 150K-240K (estimate) Senior-level Contract Full Time
Tasks
- Build CI/CD pipelines for ML workflows
- Build and operate model and inference serving infrastructure
- Build reproducible automated machine learning pipelines
- Ensure ML reliability and observability
- Implement infrastructure as code for ML systems
- Improve inference cost efficiency
- Manage machine learning deployment lifecycle
- Operate GitOps for ML workloads
- Operate agentic and LLM workloads in production
- Run ML workloads on multi tenant Kubernetes
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | AWS | AWS Bedrock | AWS EKS | Airflow | Argo Workflows | ArgoCD | Autoscaler | Autoscaling | B testing | CDC | CI/CD | Caching | CircleCI | DevOps | Experiment tracking | Feast | Feature Store | FinOps | GPU scheduling | GitHub Actions | GitLab CI | GitOps | Guardrails | IAM | Karpenter | Kubeflow | Kubernetes | LLM Inference | Lakehouse | Latency | ML observability | MLflow | Machine Learning | Model Registry | Model Serving | Multi-tenant | Multi-tenant Isolation | Networking | Object storage | Reserved Instances | SLO | SRE | Sagemaker Pipelines | Site Reliability | Spot instances | Tenant Isolation | Terraform | Throttling | Throughput
Education
N/A
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