Gcore
Gcore provides edge and cloud infrastructure for enterprises and service providers, including CDN, DNS, traffic management, security, and GPU cloud for AI workloads. It operates its own global network across six continents to deliver low-latency performance for media, gaming, and enterprise applications. Founded in 2014 and headquartered in Contern, Luxembourg, Gcore is privately held.
Open Positions at Gcore
8 open positions
Gcore is seeking a DevOps Engineer/SRE to operate and improve cloud IaaS infrastructure, including server deployment, infrastructure maintenance, monitoring, virtualization, and lifecycle automation. The role offers remote, hybrid, or office work options and exposure to globally distributed cloud and AI infrastructure.
Join Gcore’s AI Inference Operations Team as a DevOps/SRE Engineer focused on secure CI/CD pipelines, container security, and Kubernetes operations. You will help protect the software supply chain and maintain reliable infrastructure for AI-driven products.
QA Automation Engineer responsible for building scalable automated testing frameworks and quality tools for backend services and APIs. The role combines Python development, API and UI testing, CI/CD integration, and AI-assisted testing workflows.
Build Kubernetes-native AI infrastructure for scalable model inference and distributed training across GPU fleets. You’ll develop Go-based controllers, operators, APIs, CLIs, and tooling that make AI workloads faster, more reliable, and easier to operate.
Build and optimize the inference layer of Gcore’s AI platform, bringing language and multimodal models into reliable production systems. You’ll work across Python, GPU execution, inference frameworks, and Kubernetes to improve performance and efficiency.
Build Python services and APIs that manage GPU virtual machines, bare-metal servers, and cloud infrastructure at global scale. You’ll own infrastructure projects from design through production operation while improving capacity, reliability, and customer availability.
Design and operate the infrastructure powering scalable, secure AI inference workloads on-premises. This DevOps role focuses on Kubernetes, GPU scheduling, observability, automation, and high-performance computing environments.