Gcore-posted 2 months ago
Full-time • Mid Level
Town of Poland, NY
501-1,000 employees

Join a team that collaborates with industry giants like Intel, Dell, NVIDIA, Graphcore, and Equinix to accelerate AI training, provide cutting-edge cloud services, and optimize content delivery. We are over 550 professionals and currently looking for a Software Python Engineer to join our Edge Cloud Team.

  • Contribute to the development of the Everywhere Inference platform - a Kubernetes-based solution enabling scalable and portable AI inference across a wide range of environments.
  • Design and implement APIs and developer tools to simplify deployment, management, and monitoring of AI applications.
  • Focus on packaging and integrating new ML models into the platform, using Python and common ML frameworks.
  • Optimize serverless container workflows for AI workloads, ensuring performance, scalability, and seamless autoscaling.
  • Collaborate with customers to fine-tune ML model performance and support their 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, and help drive innovation within the platform.
  • Proficiency with Python, especially in the context of ML tooling or backend development.
  • Experience with AI/ML pipelines or integrating machine learning frameworks like TensorFlow or PyTorch into production environments.
  • Hands-on experience with vLLM and SGLang.
  • Familiarity with cloud-native tooling such as Docker, Helm, and related CNCF technologies.
  • A problem-solving mindset and genuine interest in working on distributed systems and platform-level challenges.
  • Clear communication skills and a collaborative attitude.
  • Solid experience with Go programming, particularly in the context of Kubernetes - including building controllers, operators, and working with custom resources (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.
  • Competitive salary
  • Flexible working hours
  • Remote, hybrid, or office work options depending on your role
  • Work from anywhere in the world for up to 45 days per year
  • Private medical insurance for you and your family*
  • 5 additional vacation days*
  • Additional fully paid sick leave days*
  • Allowance for significant life events and birthdays
  • Language classes
  • Modern office space with free snacks, drink and entertainment options*
  • Team sports activities*
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