AI Infrastructure Engineer III
USD 152K-276K (estimate) Senior-level Full Time
Tasks
- Automate AI infrastructure provisioning with Infrastructure as Code
- Build CI/CD pipelines for ML workloads
- Build scalable highly available model serving infrastructure
- Build self service AI ML platform tooling
- Deploy and operate Kubeflow MLflow KServe and Ray
- Design and operate GPU clusters for AI workloads
- Design deploy and operate AI ML platforms
- Design infrastructure for model training experimentation and feature engineering
- Implement monitoring and observability for GPU utilization and inference latency
- Manage NVIDIA GPU Operator and GPU enabled Kubernetes environments
- Optimize GPU scheduling utilization sharing autoscaling and resource allocation
- Optimize distributed GPU training performance
- Provision and manage cloud resources for AI workloads
- Troubleshoot AI infrastructure performance bottlenecks
Perks/Benefits
Skills/Tech-stack
AWS | Ansible | Azure | Bash | CI/CD | CUDA | Cloud platform | Distributed Training | ELK | GPU Operator | GitOps | Go | Google Cloud | Google Cloud Platform | Grafana | Helm | Infrastructure as Code | KServe | Kubeflow | Kubernetes | Kubernetes Helm | MLflow | Model Serving | NCCL | NVIDIA GPUs | OpenSearch | OpenTelemetry | Prometheus | Python | Ray | Terraform | “as-code”
Education
N/A
Roles
AI | AI Infrastructure Engineer | DevOps | DevOps Engineer | Engineer | Infrastructure Engineer | MLOps Engineer
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