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Software Engineer (Python, Kubernetes, AI/ML) | Gcore | Remote

2 hours, 16 minutes ago
Poland
Full-time
Senior
Backend Engineer
Software Development
Docker Go Helm Kubernetes Machine Learning Microservices MLOps Python PyTorch Serverless TensorFlow
Apply Now
Bee Talents

Bee Talents

Bee Talents is your dedicated partner in tech recruitment, saving up to 75% on standard costs. We build efficient tech teams with tailored hires for niche positions in new technologies.

Professional Services
51-250
Founded 2015
View All Jobs 8

Description

  • 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 for deploying, managing, and monitoring AI applications.
  • Package and integrate new machine learning models into the platform using Python and common ML frameworks.
  • Optimize serverless container workflows for AI workloads to improve performance, scalability, and autoscaling behavior.
  • Collaborate with customers to tune ML model performance and support their specific use cases.
  • Work with cross-functional teams to improve the AI applications marketplace and streamline model onboarding and lifecycle management.
  • Stay current with developments in Kubernetes, machine learning, and MLOps, and help drive innovation on the platform.

Requirements

  • Proficiency in Python, especially for ML tooling or backend development.
  • Experience with AI/ML pipelines or integrating frameworks such as 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 interest in distributed systems and platform-level challenges.
  • Strong communication skills and a collaborative working style.
  • Solid experience with Go programming in a Kubernetes context, including controllers, operators, and custom resources (preferred).
  • Strong understanding of Kubernetes architecture, container orchestration, and resource management at scale (preferred).
  • Understanding of GPU scheduling and performance optimization in Kubernetes (preferred).
  • Awareness of Kubernetes security practices, including RBAC and container hardening (preferred).
  • Contributions to open-source projects or involvement in cloud-native or MLOps communities (preferred).

Benefits

  • Competitive compensation.
  • Flexible working hours with hybrid or remote options, depending on the role.
  • Work from anywhere in the world for up to 45 days per year.
  • Private medical insurance for you and your family.
  • Extra paid vacation and sick leave days.
  • Support for important life moments and celebrations.
  • Language courses for professional and personal growth.
  • Modern offices with snacks, drinks, and entertainment.
  • Team sports and social activities.

Interested in this position?

Apply directly on the company website

Apply Now

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