Software Python Engineer (Cloud Inference)

AI overview

Contribute to developing a scalable AI inference platform, design APIs for AI applications, and optimize workflows using Kubernetes and machine learning frameworks.

What You’ll Do

  • 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.

What We’re Looking For

  • 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 - you enjoy working closely with others to build great solutions.

Nice to Have

  • 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.

Benefits 

At Gcore, we want you to do your best work and enjoy the journey. Our benefits are designed to support your growth, well-being, and life beyond work: 

  • Competitive compensation  
  • Flexible working hours and hybrid or remote options, depending on your role
  • Competitive compensation  
  • 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 life’s important moments and celebrations 
  • Language courses to help you connect and grow 
  • Modern, welcoming offices with snacks, drinks, and entertainment* 
  • Team sports and social activities* 

 *Benefits may vary depending on your location. 

 Equal Opportunity Employer

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. 

Perks & Benefits Extracted with AI

  • Flexible Work Hours: Flexible working hours and hybrid or remote options, depending on your role
  • Health Insurance: Private medical insurance for you and your family*
  • Team sports and social activities: Team sports and social activities*
  • Paid Time Off: Extra paid vacation and sick leave days*

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