AI Infrastructure Engineer (GPU) - Remote EMEA

📋 Description

• Build and operate production-grade model serving infra using vLLM/TGI/Triton
• Design deployment pipelines with blue/green and canary rollouts for ML models
• Develop auto-scaling systems and multi-model serving architectures
• Optimize GPU utilization, memory, network throughput, and storage
• Design observability for latency, throughput, GPU usage, and cost metrics
• Manage model registries and CI/CD pipelines for automated deployments

🎯 Requirements

• 4+ years in ML Ops, Platform Engineering, SRE, or similar infra roles
• Hands-on experience with model serving frameworks such as vLLM, TGI, Triton
• Strong background in container orchestration and production GPU workloads
• Experience with MLOps tooling including model registries, experiment tracking, and automated deployment pipelines
• Proficiency in Python and infrastructure-as-code tools (Terraform, Helm, or similar)
• Strong understanding of distributed systems, performance tuning, and production reliability

🎁 Benefits

• Take ownership of critical infrastructure powering a rapidly scaling AI platform
• Build foundational ML inference systems from the ground up
• Work at the intersection of distributed systems and GPU computing
• Gain deep expertise in next-generation AI infrastructure
• Influence engineering decisions and scalable practices