Principal ML Ops Engineer (EMEA Remote)

Stack

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 on-call responsibilities
• ▹Define engineering best practices and contribute to platform scalability

Requirements

• ▹4+ years of experience in ML Ops, Platform Engineering, SRE, 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
• ▹Ability to effectively use AI coding assistants
• ▹Ownership mindset with the ability to operate independently in a remote-first environment

Nice to have

• ▹Experience with ML platforms such as Kubeflow, MLflow, or KubeAI
• ▹Knowledge of GPU scheduling, CUDA/ROCm optimization, or multi-tenant inference systems
• ▹Experience with cost optimization across different GPU types and inference workloads
• ▹Background in early-stage startups or greenfield infrastructure projects
• ▹Proven experience building production systems from scratch rather than maintaining legacy platforms

Soft skills

About the company

Pragmatike is recruiting on behalf of a fast-scaling, well-funded distributed cloud infrastructure startup building next-generation AI-native cloud services. The company provides GPU-powered infrastructure for AI/ML workloads, secure storage, and high-speed data transfer through a decentralized architecture that significantly reduces environmental impact compared to traditional cloud providers.