Principal ML Ops Engineer (EMEA Remote)
Tasks
- Build and operate model serving infrastructure
- Design deployment pipelines
- Design observability for inference systems
- Develop auto scaling systems
- Implement CI CD pipelines for model deployments
- Implement blue green canary rollouts
- Manage model registries
- Optimize GPU utilization memory efficiency and network throughput
- Own ML system lifecycle from development to production
- Provide on-call operational support
Perks/Benefits
Skills/Tech-stack
Auto Scaling | CI/CD | CUDA | Container Orchestration | Distributed Systems | Experiment tracking | GPU Utilization | GPU scheduling | Helm | Infrastructure as Code | Kubernetes | MLOps | Memory efficiency | Model Registry | Multi Tenant Inference | Multi-tenant | NVIDIA Triton | Network Throughput | Observability | Python | ROCm | TGI | Terraform | VLLM | “as-code”
Education
N/A
Regions
Countries
Albania | Armenia | Croatia | Czechia | Estonia | Greece | Italy | Latvia | Lithuania | Malta | Montenegro | Poland | Portugal | Romania | Serbia | Spain | Turkey | Ukraine
States
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