Remote GPU AI Infrastructure Engineer

Pragmatike; Italy; Remote; EUR 120,000 - 160,000; Full time

Job summary

Pragmatike is building AI-native cloud services with a distributed GPU infrastructure, seeking an AI Infrastructure Engineer to own scalable model serving platforms. This remote-first role reports into a fast-growing startup focused on high-availability ML inference at scale.

You will design and operate core AI infrastructure, collaborate with platform and applied AI teams, and drive deployment pipelines across the stack, including observability and cost-optimized GPU utilization.

Qualifications

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

Responsibilities

• Build and operate production-grade model serving infrastructure using frameworks such as vLLM, TGI, Triton, or equivalent
• Design and implement robust deployment pipelines with blue/green and canary rollout strategies for ML models
• Develop and maintain auto-scaling systems, multi-model serving architectures, and intelligent request routing layers
• Optimize GPU utilization, memory efficiency, network throughput, and model artifact storage performance
• Design observability systems for tracking inference latency, throughput, GPU usage, cost metrics, and system health
• Manage model registries and CI/CD pipelines enabling automated and reproducible model deployments
• Own the full lifecycle of ML systems from development through production, including operational support and on-call responsibilities
• Define engineering best practices and contribute to platform scalability in a fast-moving startup environment

Skills

Python

Model serving frameworks

Kubernetes

MLOps tooling

Terraform

Helm

vLLM

TGI

Triton

Tools

Kubernetes

Terraform

Helm

vLLM

TGI

Triton

Job description

Pragmatike is building AI-native cloud services with a distributed GPU infrastructure, seeking an AI Infrastructure Engineer to own scalable model serving platforms. This remote-first role reports into a fast-growing startup focused on high-availability ML inference at scale.

You will design and operate core AI infrastructure, collaborate with platform and applied AI teams, and drive deployment pipelines across the stack, including observability and cost-optimized GPU utilization.