Software Engineer (AI/ML)

TL;DR

Software Engineer (AI/ML): Building and optimizing the Everywhere Inference platform for scalable AI deployment across diverse environments with an accent on API design and ML model integration. Focus on optimizing serverless container workflows, GPU scheduling, and ensuring seamless autoscaling for high-performance AI workloads.

Location: Remote or Hybrid in Poland, Serbia, Cyprus, or Georgia

Company

Global provider of infrastructure and software solutions for AI, cloud, network, and security, powering digital experiences via a vast global edge network.

What you will do

• Contribute to the development of the Kubernetes-based Everywhere Inference platform 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 and autoscaling to ensure performance for AI workloads.
• Collaborate with customers to fine-tune ML model performance for unique use cases.
• Drive innovation by staying current with trends in Kubernetes, machine learning, and MLOps.

Requirements

• Proficiency with Python, specifically for ML tooling or backend development.
• Experience with AI/ML pipelines and frameworks such as TensorFlow or PyTorch in production.
• Hands-on experience with vLLM and SGLang.
• Familiarity with cloud-native tooling including Docker, Helm, and CNCF technologies.
• Must be based in Poland, Serbia, Cyprus, or Georgia.
• Strong problem-solving mindset and interest in distributed systems.

Nice to have

• Experience with Go, specifically building Kubernetes controllers, operators, and CRDs.
• Deep understanding of Kubernetes architecture and resource management at scale.
• Knowledge of GPU scheduling and performance optimization in Kubernetes.
• Awareness of Kubernetes security practices, including RBAC and container hardening.
• Contributions to open-source projects in the cloud-native or MLOps domains.

Culture & Benefits

• Competitive compensation and flexible working hours.
• Hybrid or remote work options depending on the role.
• Work from anywhere in the world for up to 45 days per year.
• Private medical insurance for employees and their families.
• Extra paid vacation and sick leave days.
• Language courses, team sports, and social activities.