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

2 weeks, 6 days ago
Poland
Full-time
Senior
Backend Engineer
Software Development
Docker Go Helm Kubernetes Machine Learning Microservices MLOps Python PyTorch Serverless TensorFlow
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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 17

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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