AI Platform Engineer
Tasks
- Build model serving platforms
- Design AI inference platforms
- Design high availability architectures
- Implement autoscaling
- Implement caching strategies
- Implement monitoring observability logging
- Implement security controls authentication authorization
- Manage model deployment versioning rollback
- Optimize GPU utilization
- Optimize inference latency
- Optimize request routing traffic management
- Set up distributed tracing alerting
- Support production machine learning models
Perks/Benefits
Skills/Tech-stack
API Gateway | AWS | Alerting | Autoscaling | Azure Bicep | C++ | CI/CD | CUDA | Cloud platform | CloudFormation | Distributed Systems | Distributed tracing | Docker | FinOps | GPU Optimization | GitOps | Go | Google Cloud | Google Cloud Platform | Inference Server | Infrastructure as Code | Istio | Kubernetes | Linkerd | Logging | MLOps | Microsoft Azure | NVIDIA GPUs | Observability | Python | Ray Serve | Rust | Service Mesh | Service orchestration | TensorRT-LLM | Terraform | Triton Inference | Triton Inference Server | VLLM | “as-code”
Education
Roles
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