Requirements

• Experience with Kubernetes for deployment and development
• KubeVirt and QEMU/KVM familiarity
• Solid knowledge of internal OS architecture, Linux, and system-level understanding
• Experience or interest in hardware acceleration with GPUs, DPUs, or ARM architectures
• Proficiency in Go and C++ with concurrency, debugging, and profiling techniques

Nice to Haves

• Familiarity with NVIDIA DOCA Software Framework

What You'll Be Doing

• Building services for managing Virtual Machines on GPU servers
• Developing the Virtual Machine Scheduler across clusters with thousands of servers and GPUs

Perks & Benefits

• Competitive compensation
• Career growth and learning opportunities
• Flexibility and ownership
• Collaborative and innovative culture
• Opportunity to work on impactful AI projects
• International environment and talented teams