Software Engineer (Python, Kubernetes, AI/ML)

Gcore is a global provider of infrastructure and software solutions for AI, cloud, network, and security, operating 210+ edge locations, 50+ cloud regions, and thousands of GPUs. The company collaborates with technology partners such as Intel, NVIDIA, Dell, and Equinix, supporting digital products worldwide with a team of 550+ professionals.

• Proficiency with Python, especially in ML tooling or backend development.
• Experience with AI/ML pipelines or integrating TensorFlow or PyTorch into production.
• Hands-on experience with vLLM and SGLang.
• Familiarity with cloud-native tooling such as Docker, Helm, and CNCF technologies.
• Problem-solving mindset and interest in distributed systems and platform-level challenges.
• Clear communication skills and collaborative attitude.

Nice to have:

• Experience with Go programming in Kubernetes context, including controllers, operators, and CRDs.
• Strong understanding of Kubernetes architecture, container orchestration, and resource management at scale.
• Understanding of GPU scheduling and performance optimization in Kubernetes.
• Awareness of Kubernetes security practices including RBAC and container hardening.
• Contributions to open-source projects or involvement in cloud-native or MLOps communities.

• Contribute to the development of the Everywhere Inference platform, a Kubernetes-based solution for scalable and portable AI inference.
• Design and implement APIs and developer tools to simplify deployment, management, and monitoring of AI applications.
• Package and integrate new ML models into the platform using Python and common ML frameworks.
• Optimize serverless container workflows for AI workloads, ensuring performance, scalability, and autoscaling.
• Collaborate with customers to fine-tune ML model performance and support unique use cases.
• Work with cross-functional teams to improve the AI applications marketplace and ensure smooth model onboarding and lifecycle management.
• Stay current with trends in Kubernetes, machine learning, and MLOps to drive platform innovation.

We provide equal opportunity to all applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity, gender expression, national origin, disability, or any other legally protected characteristics.