Senior ML Ops Engineer — Remote, Scalable GPU Inference

Pragmatike; Italia; On-site; EUR 90,000 - 120,000; Full time

Job summary

Pragmatike is seeking a skilled ML Ops Engineer to design, build and operate scalable model serving for AI workloads in a fully remote, Europe/EMEA-based role. You will collaborate with infra, platform and AI teams to ensure low latency, high availability and cost-efficient inference across distributed GPU systems.

Responsibilities include deploying robust pipelines, auto-scaling, multi-model serving, and observability.

Qualifications

• 4+ years in ML Ops or similar infrastructure roles.
• Hands-on with model serving frameworks and production systems.
• Production-grade GPU workloads experience and orchestration.
• Python and infra-as-code tools (Terraform/Helm).
• Strong distributed systems knowledge and reliability focus.
• Ability to work independently in a remote-first environment.

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 rollouts 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

ML Ops

Model Serving

Kubernetes

Terraform

Python

CI/CD for ML

Distributed Systems

Remote Ownership

Remote Work

Tools

Kubeflow

MLflow

KubeAI

Job description

Pragmatike is seeking a skilled ML Ops Engineer to design, build and operate scalable model serving for AI workloads in a fully remote, Europe/EMEA-based role. You will collaborate with infra, platform and AI teams to ensure low latency, high availability and cost-efficient inference across distributed GPU systems.

Responsibilities include deploying robust pipelines, auto-scaling, multi-model serving, and observability.