Fully remote (EMEA timezone) ASAP Fluent English required Cloud Computing / AI / European Deep-Tech SaaS Pragmatike is recruiting on behalf of a fast-scaling, well-funded distributed cloud infrastructure startup building next-generation AI-native cloud services. The company is redefining how compute is delivered by providing 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. You will be responsible for designing and operating the core infrastructure that serves machine learning models at scale.

Design and implement robust deployment pipelines with blue/green and canary rollout strategies for ML models Optimize GPU utilization, memory efficiency, network throughput, and model artifact storage performance Manage model registries and CI/CD pipelines enabling automated and reproducible model deployments 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 to accelerate development and debugging workflows ~ Ownership mindset with the ability to operate independently in a remote-first environment Background in early-stage startups or greenfield infrastructure projects Take ownership of critical infrastructure powering a rapidly scaling AI-native cloud platform Work at the intersection of distributed systems, GPU computing, and sustainable cloud architecture In accordance with GDPR, your personal data will be processed lawfully, fairly, and securely, and used solely for recruitment purposes, including sharing it with our client(s) for employment consideration.

📌 Ai Infrastructure Engineer (Gpu) - Remote Emea (Madrid)
🏢 Pragmatike
📍 Madrid